Big data on the cheapest MacBook
duckdb.org386 points by bcye 4 days ago
386 points by bcye 4 days ago
I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine.
I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
> I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
Before I was a professional software developer, I used a scrawny second-hand laptop with a Norwegian keyboard (I'm not Norwegian) because that was what I could afford: https://i.imgur.com/1NRIZrg.jpeg
This was the computer I was developing PHP backends on + jQuery frontends, and where I published a bunch of projects that eventually led to me getting my first software development job, in a startup, and discovering HN pretty much my first day on the job :)
The actual hardware you use seems to me like it matters the least, when it comes to actually being able to do things.
I still manage and develop my php/jquery saas product on a 2011 27" iMac running Linux Mint, with an SSD being the only upgrade. Runs better than most new windows machines. No complaints.
I switch between Thinkpad T420s and PineBook Pro for all the hobby work.
T420s has loose USB ports and the power socket is almost falling off, so I plan to replace it by a 5 years old T14 G2 in the coming months.
I can afford the latest MacBook, but I'd rather not generate more e-waste that there is, and more importantly I feel closer to my users, and my code is efficient and straight to the point.
My non-hobby laptop is an old cheap Dell from 5-6 years ago.
The best laptop I ever had was a maxed-out Thinkpad P7x, and it came with the most meaningless job ever.
I can only compare that job to the one at a unicorn that gave me the latest and greatest MacBook. Not only the job was meaningless, the whole industry made no sense to me.
Do you have any of these meaningless jobs that come with top Macbooks to share? I am in dire need of such a job right now.
I started my business back in 2006 with an ancient 306 laptop - it was practically free, it ran VIM just fine, and that was all I needed it to do to crank out PHP until the cows came home.
My substantially more privileged, but somewhat equivalent experience, was doing mobile app development, Docker, linux VMs, UI design, and finding out about hacker news on an 11 inch MacBook Air with 4gb of RAM.
i have a computer that benchmarks literally 10x faster and with 32x the amount of RAM, but i miss that little thing that helped me build my career from nothing
My dad spun up my Pentium Deschutes (400MHz!) machine the other day. Same hard drive from when I was 10 years old. “clouds.psd” was on the desktop.
I still remember retiring that computer. The first thing I did when I got my Pentium IV chip a year later was download Macromedia Dreamweaver. Did me well.
I do most of my work remotely on a little Raspberry Pi 4 server attached to my home ISP: https://fatcity.it/
But I'm planning to do a big jump: Soon I will switch to a 2012 Mac Mini as my primary linux server!
I wrote 99% of a large PHP app on an six year old laptop with a single 17" LCD. Meanwhile, at my desk, I had a Dell workstation with 3 monitors at the time, but it was easier to squirrel away in a corner somewhere, undisturbed.
After all, the actual server ran the code, I just needed text editors, terminal windows, and web browsers.
Your hardware matters quite a bit if you're doing lower level things and the architecture is not the same as you're developing for. But apparently HN is all web devs
Unless you want to insmod things in your main kernel like a cowboy, I don't see why you'd need architectures to match. Cross compilation is the proper way (for some architectures it would be quite hard to find a machine capable of compiling the kernel before the heat death of the universe...)
I just spent vacation deciding not to bring a laptop, but to use my android phone (a galaxy s22) with a hdmi adapter and Bluetooth travel keyboard. Plugged it in to the TV in our accomodation and had a lot of fun.
Running neovim on termux was fine. Developing elixir was no problem, the test suite took 5s on my phone, and takes 1s on my laptop. Rust and cargo compiling was slow enough that I didn't really enjoy it though.
Meant that I could just pack up instantly and have an agent do review workflows while I was out and about as well in my pocket, and didn't really notice a big battery hit.
Interesting vacation activities.
Ikr. Vacation for me would be : get away from electronics as much as possible. Maybe stay connected with family or do payments but not beyond that.
I don't really enjoy compiling rust on my M2 Pro, so I wouldn't necessarily blame the phone
Local LLMs and compiling rust are the only two things that I have seen saturate my M4 Max, hahaha.
I brought my 13 inch macbook pro to japan for three weeks last month for photo editing. i was able to pack up immediately by slipping it into my backpack laptop pocket.
Not sure the difference other than weight, but I wasn't carrying it day to day when i could leave it in my hotel room.
And nowadays we have Debian running in a VM on Android [1]
[1] https://www.zdnet.com/article/how-to-use-the-new-linux-termi...
This doesn't really sound like a vacation.
Seems like vacation from things you have to do to things you enjoy doing.
Exactly that, I have too many ideas for side-projects and never enough time for them.
The main activity was still the traveling, hiking and enjoying some calm time. But instead of spending the usual downtime reading or something else, I had a blast coding and experimenting.
According to Google AI > A vacation (American English) or holiday (British English) is a designated period of time for rest, recreation, or travel, often taken away from home. It involves a break from work or school routines, usually lasting several days or weeks. Vacations are crucial for mental health, reducing stress, and fostering better relationships.
So maybe different meaning for everyone. For me it’s getting away from technology and into nature.
> a break from work... are crucial for mental health
When I'm hacking on my Linux desktop automation scripts on my free time, I can assure you that my good mood is positively contributing to my mental health.
> So maybe different meaning for everyone.
Indeed.
It's starting to show its age, but I've been using a 2019 MacBook Pro with the Intel chip and 16GB of memory. Still handles multiple terminal sessions with Claude Code and Codex simultaneously, building in Xcode, running Docker in the background, etc.
(Maybe the fans sometimes sound like they're a jet engine taking off…)
Finally just put an order in for a new 16" MBP M5 Max with 48GB memory only because it looks like they're going to stop supporting the Intel stuff this year and no more software updates. It'll probably be obsolete in six months with the rate things are going, but I've been averaging seven years between upgrades so it should be good!
Oh my. All I have to say is cherish the first week of your M* experience. :D When I got rid of my intel MBP (it was an i7) for my MBA it was astonishing how fast and smooth it was.
So, the m5 with 48gb of ram will be amazing.
Hah. yeah. I went from a 64GB i9 to a 32GB M2, and it was night and fucking day
I agree. It was utterly ridiculous how noticeable the improvement was. I was doing z3 solving for ICFP contest the first couple weeks after getting the m1 air. And it was consistently smoking my teammates maxed out i7 MBP
Well, Claude Cod and Codex should be doing most of their heavy lifting in the cloud?
Sort of, they have no "hands", LLMs can only respond that they want to execute a tool/command. So they do that a lot to: read files, search for things, compile projects, run tests, run other arbitrary commands, fetch stuff from the internet etc.
Obviously the LLM inference is super heavy, but the actual work / task at hand is being executed on the device.
yeah I run Claude code on a 2013 Mac book air that refuses to die, I don't think it's very compute heavy.
Still using that 2019 MBP (16 inch, 16G memory) as a daily work machine.
Is still handling the load well, though at times, fans get quite loud, especially with all the background processes and VM setups.
Hope to get a new MBP this year, as being on Intel means lots of software that won't run on it (ie, Codex app for example, won't run on Intel Macs)
Former employee of mine had the 2019 MBP as well. After a few years he had the same problem with the fans -- if you haven't already, pop it open and clean the fans and vents. You'll probably need a little brush along with compressed air. Lots of stuff comes up on Google. Great machine btw. Good luck!
Thanks for this tip! The fans of mine have been spinning up regularly, especially noticeable when I upgraded to Tahoe a few days ago.
I use a 2015 MacBook Pro all the time--like right now. It does have 16GB of memory. It's what sits on my dining room table where I do most of my writing/browsing and which I take for travel. I do have an Apple Silicon MacBook Pro in my office but my downstairs "office" is a lot lighter and airier.
I use a 2015 MacBook Pro all the time--like right now.
I have a 2010 MacBook Air that I still use when traveling.
The battery is completely shot, but it works fine when plugged in. And if I'm on the road, I don't use my computer until I get to the hotel anyway. And even then, it's just fine for e-mail, browsing, and even Photoshop.
I think this one had a battery replacement because it was bulging. But it's definitely in the class of devices that, if it gets swiped or lost, is basically in the <ehh> category as opposed to my newer one.
Am probably giving newish iPad and magnetic keyboard a spin on my next trip mostly to see how it goes.
I have one of these (it's my only Mac), but it only has 2GB of RAM, so it's kinda rough. I tried Mint on it, but IIRC it might not have the GPU drivers? I just bought it a new SSD which helped a bit.
I was using a M1 Mac Mini and only 8GB of RAM on it to build iOS apps for maybe a year. It's absolutely doable, though it very noticeably gets a little less snappy when building projects. When building in Xcode and then switching to Firefox to browse for instance, I could tell it took slightly longer to switch tabs and YouTube playback would occasionally stutter if too much was happening.
I also was using an Intel MacBook Pro with 16GB at the time. Doing the same thing there was much smoother and snappier. On the whole, it actually made me want to just the laptop instead since it "felt" nicer. (This isn't measuring build times or anything like that, just snappiness of the OS.)
I'm glad enough people got M1 MacBook Airs now that the broader sentiment within the commentariat is changing and people are pushing back on the dismissals.
8gb has ALWAYS been fine in Apple Silicon Mac OS. RAM usage on a fresh boot is a meaningless statistic (unused RAM is wasted RAM). And they're just plain capable!
People usually forget 8GB isn't 8GB. Memory compression means you can store ~2x (lz4) to 3x (zstd) as much data in memory as ordinarily. And in the worst case, reading swap from disk (writes don't matter as they can be predicted) is so much faster with NVMe SSDs.
The worst corner they cut is no keyboard backlighting. That saves them what, $1 BoM per MacBook Neo? Especially because now they have to put up an entire new keyboard production line instead of just piggybacking off of the Air keyboard production line.
This is PR speak.
No 8GB, compressed or whatever was not enough for MacOS when M1 was released. Even for simple outlook, web browser, excel type of workflows.
After 3-4 hours of work, the window manager process itself is consuming gigabytes of memory. Not even considering any browser or electron apps.
My M1 Mac mini was choking up so much that I had to trade it in. That was back in 2021. Today apps are even more bloated.
Yeah, you never owned a Mac and are just making stuff up. I have no urge to debate zealots. Bye.
I am not the one claiming that apple does magic with memory. FYI right now I just opened monitor (M1 16GB) and sorted by memory:
1. WindowServer : 4.33GB 2. Safari pages (~10 open): ~ 5GB (monitor reports per tab) 3. Outlook: 1.45 GB 4. VS Code: 1.43 GB 5. Excel: 1.25 GB
Swap Used: 6.46GB.
Memory pressure is already orange and machine is slow.
It's not cost saving, it's deliberate differentiation.
Isn't it definitionally both?
Of course. At the same time, the cost saved is so little that you can reasonably discount it as being a meaningful contributing factor in this case.
I just retired my m1 air to being a server this month. They’re very capable laptops. If the neo is even comparable in spec it’s excellent for the price
My m1 air with 1TB ssd and 16GB of ram is a little champion, I use it during travel to play indie games like Hades II or Slay the Spire, and it works really well, better than my Steam Deck which broke. The only issue it really has is when I try to plug it into my docking station it struggles mightily with 2 2K screens and a 4K screen, so I just use my desktop in that case.
I am jealous of my wife’s 13” M5 iPad Pro though, that oled screen is gorgeous, a wonder of modern engineering.
> [...] and it works really well, better than my Steam Deck which broke.
Well, the MacBook Air was also a lot more expensive than the Steam Deck?
I just bought a second hand M1 64GB as my main work laptop, haha. They definitely are capable laptops
Yeah! My M1 air is now my iOS build server since GH actions bill macOS mins at 10x the price.
How do you use M1 Air as iOS build server. Is 8G sufficient for only doing iOS builds? Do you connect to it remotely?
Couls you please describe your dev process.
It works out pretty okay for me, I do it since GH runners are very expensive and I have my own hardware so why not. https://docs.github.com/en/actions/concepts/runners/self-hos...
I setup a self hosted runner and then use that in my CI workflows. Then I disabled it from sleeping so it can clamshell forever and now it sits here in my living room silently workin' https://imgur.com/a/EaBICdo
why does GH actions bill macOS minis 10X?
Ah sorry minutes, they bill the most for macOS probably because of what a pain it is to scale it with apples EULA (I'm guessing) https://docs.github.com/en/billing/reference/actions-runner-...
Mins here being short for minutes, not minis.
And, presumably for a combination of the Mac build (and hardware) being of niche interest and sitting outside the standard Linux workflows so it's annoying to administer. And serving a money-making audience (iOS app devs) who have a revenue stream and see the extra CI cost as worth it.
It will do real work fine. But slack and a browser will bring it to its knees.
I have an older 8GB MacBook Air. This is false. I routinely have Slack, Chrome, iTerm, Visual Studio Code, and more open on it. It’s fine.
Those apps don’t need every single byte of memory you see in Activity Monitor to be active in RAM all of the time. The OS swaps out unused parts to the very fast SSD. If you push it so far that active pages are constantly being swapped out as apps compete then you start to notice, but the threshold for that is a lot higher than HN comments seem to think.
It really isn't. It is a capable machine but modern software has made it a lemon. And that is the only reason apple sells it. So that whoever buys it needs to buy another one prematurely, generating another sale.
Everything from apple to modern software is rotten to its core.
It really isn't.
…in reply to someone who just said their experience is fine, and included details. If you just want to rant about Apple, have at it, but you’re going to have to do better than “nuh, uh” if you want to be convincing.
Well I could say that it isn't enough for vscode alone. And I'd be right. It all depends on how and what you use vscode for.
8GB really shouldn't be an option in 2026, it is just shortsighted and an insanely uneven build.
I could rant about Dell too. Or most other manufacturers (surprise, greed isn't apple exclusive). But Apple at least tries to keep the appearance of a higher profile.
Well I could say that it isn't enough for vscode alone. And I'd be right. It all depends on how and what you use vscode for.
Fair enough; though experience says 8Gb will run VScode, it would very much depend on the use case, I agree. OTOH, I would argue that anyone working VScode that hard probably isn’t buying 8Gb machines, but OP did say they’re running it so it’s up for discussion.
I’m sick to death of this. It’s so devoid from reality in 2026 that I see it as a lowest common denominator populist political catchphrase more than any legitimate contributor to any conversation. My min spec MacBook Pro from 6 years ago doesn’t flinch at this, and it barely flinches at a whole lot more.
Can we please just move on? Maybe get your hardware checked if you’re legitimately still having these issues.
Only if you insist on running the standalone slack app for some reason. Why run one instance of Chrome when you can pay for two?
I've been finding it hard to wean myself off the standalone app but another major reason to do so is opening threads in separate tabs. I find as soon as I'm involved in two or more conversations on there it's super easy to start losing track of things.
Maybe if you have 100 browser tabs or something silly like that?
A couple YouTube tabs are enough if you leave them running for long enough. Just one YT browser process will easily take up 1-4GB sooner or later.
Or it won’t because Chrome and MacOS will know how much RAM is available and manage it effectively.
I am talking from experience with an M1 & 8GB RAM. I had to restart either the browser or the YouTube browser processes at least once every couple days to stop the whole system from lagging.
A couple Facebook Marketplace tabs that have videos of the item for sale would absolutely crush my 2017 MacBook Pro.
My M1 Air would slow down a little, but was still usable doing the same thing. And they both had 8GB of memory.
While I agree with your statement, I don't think judging one's way of working and using their computer was necessary.
I could have two browser windows open in the late 1990s. I have about a thousand times as much RAM now. So even with 10x more bloat in the pages, I should be able to open 200 tabs just fine.
The argument is misrepresented - I think it's about frustration and convenience, not achievability.
I developed some work that keeps tens of thousands of people alive every day on a $100 Acer netbook almost 15 years ago. The tools are always there, I don't think anyone thinks the work is actually impossible to do on a limited machine.
I wrote a fix for node that got upstreamed a few years ago on a Lenovo Thinkpad 3 Chromebook. I'm actually commenting from it now. It's not a workhorse by any means, but for $99, it's not bad. A 1.1GHz Celeron processor with 4GB of memory is able to compile projects like node, python, Erlang, etc. without much hassle. It just takes a lunch break :)
Any modern Mac is more than capable. I had the baseline M1 Macbook Air that I did work on as well, just to see how that fared. Much better than this machine - 10x the price, but more than 10x the performance. This one is great as a "I don't mind if I break it or lose it" device.
8gb of memory is the issue. I regularly catch the window manager consuming more than 8gb on my 16gb machine.
Also a browser sneeze takes more than 4gb.
I was doing Android development and Verilog synthesis on a mobile Nehalem i5 in 2020. That machine is still totally adequate for anything a "normal person" does with their computer, provided they have good tab hygeine. The reality is that (unless you play video games and/or you want local LLM inference) the demands people place on their computers haven't changed significantly in at least 10 years.
I know it's not really related, but how did you manage to build two startups worth getting acquired in such a short period of time?
Oh that made it seem like I was the driving factor. Maybe for the first one (Percy.io) I can claim a large part of that success (owning the SDKs and support end to end).
The other I just owned the front end infra and was on the growth team. The rest of the folks were the stars on that one.
Edit: I guess I brought that up because I guess I don't know any more "real work" that that, ha. What is 'real work'?
It didn’t look like bragging, if that’s what you were worried about. Thnaks for answering :)
> I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine.
But... you can do the same exercise with a $350 windows thing. Everyone knows you can do "real dev work" on it, because "real dev work" isn't a performance case anymore, hasn't been for like a decade now, and anyone who says otherwise is just a snob wanting an excuse to expense a $4k designer fashion accessory.
IMHO the important questions to answer are business side: will this displace sales of $350 windows machines or not, and (critically) will it displace sales of $1.3k Airs?
HN always wants to talk about the technical stuff, but the technical stuff here isn't really interesting. The MacBook Neo is indeed the best laptop you can get for $6-700.
But that's a weird price point in the market right now, as it underperforms the $1k "business laptops" (to avoid cannibalizing Air sales) and sits well above the "value laptop" price range.
No, you can't do real work on a $350 windows machine. No way such a setup is suitable for anything beyond browsing a tab or two and connecting to servers using SSH.
And, the whole shittiness of the experience will even distract you attempting real work: the horrible touchpad, the bad screen, the forced windows updates when you trying to start the machine to do something urgent, ads in Windows, the lack of proper programmability of Windows (unless you use WSL).... Add the fact that the toy is likely to break in a year or two. These issue exist on far more expensive Windows machines, how much more a $350 machine.
Leaving Windows machines and OS behind for more than a decade has been a continuing breath of fresh air. I have several issues with the Apple devices and macOS (as I have with Linux too), but on the whole they are far better than Windows. The only good thing about Windows that I miss on Macs is the file explorer and window management, not sure why Apple stubbornly refuses to copy those.
A lot of $350-ish Windows machines also don’t have SSDs but instead eMMC storage, which is dog slow and will make modern SSD-mandatory Windows feel even more awful to use.
If Windows/Linux/x86 is non-negotiable and that’s your budget, I would never in a million years recommend anything brand new. This is when you go pick up a $350 used midrange ThinkPad on eBay. It won’t outperform a Neo in terms of CPU and battery life but I guarantee it’ll be a better experience than the garbage routinely sold at this price point.
Of course you can. You can do real work on an $80 Amazon Fire. Yes, some things will be potentially impossible or frustrating but that's also true of the MacBook Neo, just a bit higher of a bar. A lot of this also depends on your definition of "real work".
$350 USD can get you a decent laptop with a SSD, 16GB RAM and something like an Intel N100 or N95. And they pretty comparable to a decent Intel Skylake CPU which are still pretty usable.
https://www.amazon.com/NIAKUN-Computer-Processor-Keyboard-Fi...
https://www.amazon.com/AOC-Computer-Processor-Laptops-Window...
Yes, the Neo has a faster CPU but it also has less RAM and less storage and costs more and has less ports. Besides ray traced games what can the Neo do that the others can't? They'll take longer but they'll get there.
And if you're willing to go used? That $350 goes a lot further.
> Yes, the Neo has a faster CPU but it also has less RAM and less storage and costs more and has less ports.
8GB on Apple Silicon is far better than 16 GB on Wintel, and I don't event trust the quality of 16GB of RAM on a bottom of the barrel Windows machine.
Would you prefer a machine that is still good 7 years from now with less ports, or one with more ports that you have to replace in 2 years? Yes it is more expensive now, but over 7 years it is an absolute bargain.
16 GB physical RAM is just better. Apple isn't magic. Gimme a break. Both devices have SSDs for fast swapping and have RAM compression. You can't spin up a VM that has 8GB RAM on the Neo, you can't load a large spreadsheet or do a decently sized digital painting. I could maybe buy a claim that 8GB is better on Mac than 8GB on Windows.
Why would you have to replace it in 2 years? How do we know Apple will even be offering updates to Neo in 7 years? Will 8GB still be usable in 7 years really? 8GB is barely on the fence already.
I wouldn't be surprised if Apple drops the Neo from software support in less than 7 years.
The ThinkBook 14 Gen 6 at Costco for $380 has a single thread passmark score of 2800. The laptop I use to develop most of my SaaS products, with IDEs and claude open etc, has a score of 2000. I run Linux, but win10 iot runs fine on it too.
> No, you can't do real work on a $350 windows machine.
Sigh. I mean, even absent the obvious answers[1], that's just wrong anyway. You're being a snob. Want to run WSL? Run WSL. Want to run vscode natively? Ditto. Put it on a cheap TV and run your graphical layout and 3D modelling work. I mean, obviously it does all that stuff. OBVIOUSLY, because that stuff is all cheap and easy.
All the complaining you're doing is about preference, not capability. You're being a snob. Which is hardly weird, we're all snobs about something.
But snobs aren't going to buy the Neo either. Again, the business question here is whether the $350 junk users can be convinced to be snobs for $600.
[1] "Put Linux on it", "All of your stuff is in the cloud anyway", "It's still a thousand times faster than the machine on which I did my best work", etc...
You mean that machine from 30 years ago that was running 30 year old software that has nothing in common with today’s development? And how well does Linux run on 4GB?
So weird to see this kind of flaming more than a decade after it got stale and silly. I mean, yeah, kinda: a 64MB K6-300 was pretty great!
But as to the 4G quip, that's showing some ignorance of where the market is. The value segment is filled with devices like this: https://www.amazon.com/HP-Stream-BrightView-N4120-Graphics/d...
That's a 16G windows box which will happily run multiple VMs for whatever your deployment environment is, something the Neo is actually going to struggle with. The Jasper Lake CPU is indeed awfully slow, but again for routine "dev" tasks that's just not a limit.
You would obviously refuse out of taste, but if you were actually forced to use this machine to do your job... you absolutely could.
It would have been a better fit for me than the M4 Air, I literally use it only for typing and browsing, plus a could of Mac-only tools. Brilliant machine but complete overkill for me. It's almost tempting to switch just to get rid of the display notch.
Nice, you beat me to this concept. I finally planted a flag and decided to dev entirely on an M3 with 8Gb.
It is completely feasible, and the battery life - amazing. Even when running a whole pile of Kubernetes services.
I'm still doing iOS dev on my 2020 M1 MPB, and it's fine! I expect that if I change out its battery and apply new thermal paste it would run for another 6 years.
All of FastComments is/was built on an 8th gen i7 from 2017
Using older hardware has helped me not accidentally build slow stuff. Although at some point I gotta upgrade and just add more performance tests :) but nothing replaces feeling it yourself.
Can you say a little more about what you mean by "better"? How much faster is editing?
Better in terms of raw specs. The original M1 Air also came with 8GB of RAM, and the A18 Pro in the Neo is faster than the version of the M1 that shipped in the base model Air
most dev workflows from pre 2021 can probably run just fine on a NEO - i think once you get into conductor / 8 terminals with claude code territory that’s where things start to slow down
i just got an m5 max with 128gb of ram specifically to run local llms
Does Claude Code take up that many local resources? I thought the heavy lifting was in the cloud?
Claude Code still runs things on your local machine. So if you have some pretty expensive transpilation, or resolving dependency trees that needs musl recompilation, or doing something rust, you still need a reasonable ammount of local firepower. More so if you're running multiple instances of them.
Heh, I also upgraded to run local LLMs. As a tiny aside, codex does not burn resources like CC does.
Would say get one with a fan, my small react native app building/indexing in xcode takes several minutes on a 2020 M1 macbook air
But damn I like that design
> just to show people it’s not this handicapped little machine
I used to think this way about Apple and its jarring to read with it 10-15 years behind me.
It reads as aggro and oddly tribalistic / sports fan-y.
(what people? who thinks its slower than an M1? who thinks you can't code on it? what will you coding on it prove to these people that the benchmarks they read can't? with all that, why get so invested you're buying a machine you don't want to use day to day? what does "handicapped" mean in this context?)
Only sharing b/c I never understood why people would roll their eyes at me, and apparently I finally reached my own graybeard moment, and I am now rolling my eyes at both of my selves :)
It’s fine to if you don’t have any memory hogging apps. But as soon as you fire up a couple demanding Docker containers you’ll feel the pain. 8GB isn’t so much RAM for some applications.
Why do you think people buying the cheapest MacBook available will be running Docket? Do you commonly run Docker containers on the cheapest Windows laptop available? Why not?
[flagged]
delete pls
I dunno, I'm more afraid of the syndrome where people seemingly stop reading after a word or two, instead of reading/listening to the full context and then understanding that maybe they'll explain what they mean by that later on.
Besides, almost starting to feel like something LLMs cannot replicate as easily, being strongly worded, it's a bit harder to coax commercial LLMs to be "mean" towards people, so if someone is "strongly opinionated", it almost makes the comment feel more human-like. But I digress.
Sometimes the truth is succinct.
If someone would call Apple customers idiots, would they get banned for breaking HN rules? After all, they were the ones who kept buying generations of overpriced overheating intel garbage with keyboard that would break from spec of dust. Would that not also be the truth?
Then why is it OK to call other people, Mac Neo skeptics in this case, idiots?
>If someone would call Apple customers idiots, would they get banned for breaking HN rules?
No. There's no shortage of comments of HN that do exactly that.
In fact, you just imply exactly that regarding them buying "overpriced overheating intel garbage with keyboard that would break from spec of dust".
Been using Wintel and Mac laptops for 30 years, and, crap keyboard aside (itself an overblown concern, had those for 5 years and never got it stuck) my Intel MBPs were still great laptops, and nothing in the Wintel world was as good except some Lenovo machines (which were good in ways the Mac laptops weren't but also the opposite).
>Then why is it OK to call other people, Mac Neo skeptics in this case, idiots?
For the same reason the previous case is.
> There's no shortage of comments of HN that do exactly that.
Then you should have no shortage of examples to show as proof.
>In fact, you just imply exactly that
I didn't call anyone an idiot. The implication is on your interpretation. Meanwhile the comments I was replying directly called people idiots. If you can't make a distinction, I don't know what else to say.
>For the same reason the previous case is.
Previous case isn't. You get banned if you call people idiots on HN. Double standards hypocrisy.
>Then you should have no shortage of examples to show as proof.
I'm not your search engine. If you're on HN long enough, you should have already seen a fair share of comments calling Apple users (and basically any other tech target group) names. Here's from a random 1-second search:
https://news.ycombinator.com/item?id=46812578
>Previous case isn't. You get banned if you call people idiots on HN
Must be new here.
When I teach, I use "big data" for data that won't fit in a single machine. "Small data" fits on a single machine in memory and medium data on disk.
Having said that duckDB is awesome. I recently ported a 20 year old Python app to modern Python. I made the backend swappable, polars or duckdb. Got a 40-80x speed improvement. Took 2 days.
The funny thing is that those days you can fit 64 TB of DDR5 in a single physical system (IBM Power Server), so almost all non data-lake-class data is "Small data".
And a single machine can hold petabytes of disk for medium scale. There aren't many datasets exceeding that outside fundamental physics.
> There aren't many datasets exceeding that outside fundamental physics.
Just about every physical world telemetry or sensing data source of any note will generate petabytes of analytical data model in hours to days. On the high end, there are single categories of data source that aggregate to more like an exabyte per day of high-value data.
It is a completely different standard of scale than web data. In many industrial domains the average small-to-medium sized company I come across retains tens of petabytes of data and it has been this way for many years. The prohibitive cost is the only thing keeping them for scaling even more.
The major issue is that the large-scale analytics infrastructure developed for web data are hopelessly inadequate.
You could generate PB of data from a random number generator.
My question would be, why does a company need PBs of sensor data? What justifies retaining so much? Surely you aren’t using it beyond the immediate present.
There's nothing wrong with that. Small data is relative, and my clients often find it useful to rent or get access to beefy machines to process it with "small" techniques rather than use clusters...
I'm curious - what were you doing that polars was leaving a 40-80x speedup on the table? I've been happy with it's speed when held correctly, but it's certainly easy to hold it incorrectly and kill your perf if you're not careful
Polars is fastest when you avoid eager eval mid-pipeline. If you see a 40x gap it's often from calling .collect() inside a loop or applying Python UDFs row-wise.
20 year old BI app. Columnar DBs weren't really a thing. (MonetDB was brand new but not super stable. I committed the SQLAlchemy interface to it.)
KDB v1 is from sometime in the late 1990’s (I met v2 in 2002; but v1 was internal use only at some investment bank).
But that follows A and A+ which were extremely column oriented and date to early 1990s or even late 1980s ; and to various APL implementations going back to the 1960’s
Columnar DBs were very much a thing among APL users (finance and operations research) but weren’t really known outside those fields - and even in those fields, there was a period of amnesia in the late ‘90s/early 2000’s
Might be tangential but in my recent experience polars kept crashing the python server with OOM errors whenever I tried to stream data from and into large parquet files with some basic grouping and aggregation.
Claude suggested to just use DuckDB instead and indeed, it made short work of it.
A bit of a moving target there, especially with the definition of medium data on disk considering the rise of high speed NVMe vs spinning metal. Makes me wonder if the 00s 'Big Data' era and the resulting infra is largely just outdated now...
Always a classic: https://yourdatafitsinram.net/
Outside of the king's ransom you now have to pay for it, you can fit 99% of problems into RAM.
This is as much an indictment of AWS compute as it is anything else.
Kinda comparing apples to oranges. AWS was using EBS and not local instance storage. So you’re easily looking at another order of magnitude latency when transmitting data over the network versus a local pcie bus. That’s gonna be a huge factor in what I assume is a heavy random seek load.
I wrote a longer comment already (https://news.ycombinator.com/item?id=47352526) but looking at the hot run performance and making big hand wavy guesses, the performance difference might not be as big as you'd expect.
But AWS beat the laptop? And there's no cost to performance analysis? Yes AWS is overpriced but how do you make that conclusion from this specific article? Because network disks were slower than SSDs? AWS also has SSD instances with local storage.
I haven't tried the newer I7i and I8g instance types (the newest instances with local storage) for myself, but AWS claims "I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances."
I benchmarked I4i at ~2GB/s read, so let's say I7i gets 3GB/s. The Verge benchmarked the 256GB Neo at 1.7GB/s read, and I'd expect the 512GB SSD to be faster than that.
Of course, an application specific workload will have its own characteristics, but this has to be a win for a $700 device.
It's hard to find a comparable AWS instance, and any general comparison is meaningless because everybody is looking at different aspects of performance and convenience. The cheapest I* is $125/mo on-demand, $55/mo if you pay for three years up front, $30/mo if you can work with spot instances. i8g.large is 468GB NVMe, 16GB, 2 vCPUs (proper cores on graviton instances, Intel/AMD instance headline numbers include hyperthreading).
The article is literally saying the opposite. Quote:
> Here's the thing: if you are running Big Data workloads on your laptop every day, you probably shouldn't get the MacBook Neo.
> All that said, if you run DuckDB in the cloud and primarily use your laptop as a client, this is a great device
Yeah, this is really about how ludicrously overpriced big cloud is. I’ve got a first gen M1 Max and it destroys all but the largest cloud instances (that cost its entire current market value per month!), at least in compute. It’s a laptop! A decent bare metal server in a rack will destroy any laptop.
It’s staggering. Jaw dropping. Bandwidth is even worse, like 10000X markup.
Yet cloud is how we do things. There’s a generation or maybe two now of developers who know nothing but cloud SaaS.
I watched everyone fall for it in real time.
> I’ve got a first gen M1 Max and it destroys all but the largest cloud instances (that cost its entire current market value per month!)
You're either underestimating how big cloud instances can get or overestimating how much it costs to rent a cloud instance that would beat an M1 Max at any multi-core processing.
According to Geekbench, the M1 Max macbook pro has a single-core performance of 2374 and multicore of 12257; AWS's c8i.4xlarge (16 vCPUs) has 2034 and 12807, so relatively equivalent.
That c8i.4xlarge would cost you $246/mo at current spot pricing of $0.3425/hr, which is, what, 20% of the cost of that M1 Max MBP?
As discussed recently in https://news.ycombinator.com/item?id=47291906, Geekbench is underestimating the multi-core performance of very large machines for parallelizable tasks -- the benchmark's performance peaks at around 12x single-core performance. (I might've picked a different benchmark but I couldn't find another benchmark that had results for both the M1 Max and the Xeon Scalable 6 family.)
If your tasks are _not_ like that, then even a mid-range cloud instance like a 64-vCPU c8i.16xlarge (which currently costs $0.95/hour on the spot market) will handily beat the M1 Max, by a factor of about 4. The largest cloud instances from AWS have 896 vCPUs, so I'd expect they'd outperform the M1 Max by about 50-to-1 for trivially parallelizable workloads. Even if you stay away from the exotic instances like the `u7i-12tb.224xlarge` and stick to the standard c/m/r families, the c8i.96xlarge has 384 vCPUs (so at least 24x the compute power of that M1 Max) and costs $3.76/hr.
> That c8i.4xlarge would cost you $246/mo at current spot pricing of $0.3425/hr, which is, what, 20% of the cost of that M1 Max MBP?
A 5 month ROI on a hardware investment would be excellent, so not sure what you're trying to say here?
I agree and disagree, the benefit with cloud is you "don't need to manage it", it scales automatically, redundancy, and automatic backups etc. I do think you are right; in the future there will be more infrastructure as code as cost pressures become more obvious.
Those benefits are at least partly lies though.
The tooling — K8S with all its YAML, Terraform, Docker, cloud CLI tools, etc. — is pretty hideously ugly and complicated. I watch people struggle to beat it into shape just like they did with sysadmin automation tools like Puppet and Chef a decade or more ago. We have not removed complexity, only moved it.
The auto scaling thing is a half truth. It can do this if you deploy correctly but the zero downtime promise is only true maybe half the time. It also does this at greatly inflated cost.
Today you can scale with bare metal. Nobody except huge companies physically racks anymore. Companies like Hetzner and DataPacket have APIs to bring boxes up. There’s a delay, but you solve that by a bit of over provisioning. Very very few companies have work loads that are so bursty and irregular that they need full limitless up and down scaling. That’s one of those niche problems everyone thinks they have.
The uptime promise is false in my experience. Cloud goes down for cluster upgrades and any myriad other reasons just as often as self managed stuff. I’ve seen serious unplanned outages with cloud too. I don’t have hard numbers but I would definitely wager that if cloud is better for uptime at all it’s not enough of an improvement to justify that gigantic markup.
For what cloud charges I should, as the deploying user, receive five nines without having to think about it ever. It does not deliver that, and it makes me think about it a lot with all the complexity.
The only technical promise it makes good on, and it does do this well, is not losing data. They’ve clearly put more thought into that than any other aspect of the internal architecture. But there’s other ways to not lose data that don’t require you to pay a 10X markup on compute and a 10000X markup on transfer.
I think the real selling point of cloud is blame.
When cloud goes down, it’s not your fault. You can blame the cloud provider.
IT people like it, and it’s usually not their money anyway. Companies like it. They’re paying through the nose for the ability to tell the customer that the outage is Amazon’s fault.
Cloud took over during the ZIRP era anyway when money was infinite. If you have growth raise more. COGS doesn’t matter.
Maybe cloud is ZIRPslop.
With cloud, what you're really paying for is flexibility and scalability. You might not need either for your applications. At some startups, we needed it. We sized clusters wrong, needed to scale up in hours. This is something we wouldn't ever be able to do with our own hardware without tons of lead time.
If your application won't ever require more resources than a single server or two, then you are better off looking at other alternatives.
Honestly I think the best path is hybrid with the cloud as DR and sudden load scaling.
Metal with data streamed to cloud and cloud as hot backup is something some people already do.
If the metal dies in a catastrophic way (multiple nodes at once and loss of quorum, catastrophic DC outage, etc.) you spin it up in AWS.
as a broke ecologist, this little computer can do everything I need in R and word and is a phenomenal build for the price. I'm really enjoying it thus far.
How did you get one already? I thought they were just up for pre-order
Shipping started yesterday, meaning preorders would already have arrived then
I take it you're researching clams? Or you happen to like clams a lot?
Where I live, our government-funded clam research programs are mostly shutting down. Very sad.
I adore DuckDB.
Did a PoC on a AWS Lambda for data that was GZ'ed in a s3 bucket.
It was able to replace about 400 C# LoC with about 10 lines.
Amazing little bit of kit.
I lost trust of DuckDB's test after https://duckdb.org/2024/12/06/duckdb-tpch-sf100-on-mobile#a-..., they were comparing apples with bananas, well actually Swift app on iPhone vs CLI app in a terminal.
> CLI app in a terminal
The terminal and CLI app within ran locally on a smartphone, which was the premise of the experiments within the linked post.
They also weren't comparing a Swift app on an iPhone with their Android run, they were comparing both against "... the system in the research paper that originally introduced vectorized query processing[.]"
This is awesome.
I wish more companies would do showcases like this of what kind of load you can expect from commodity-ish hardware.
[flagged]
I never met someone using Apple laptops professionally who thought it was a status symbol. I only keep hearing this from non-Apple users.
The only status it brings is "smart enough to not use Windows 11" or "cares enough to get the work done rather than fighting with Linux on laptops".
(I use Linux on desktop as a first choice, but it's always been an uphill struggle with laptop wifi/power manglement/audio for me. I blame the esoteric chipsets used in the machines I've bought in the UK)
This brand's perception varies wildly between different income groups, but is still one or the other flavor of positive in the end.
I have blue collar friends in California that consider apple products a sign of leftism and I hate to say it, but even sexuality (but that moreso in a joking way.)
Its because its frowned upon to say it out loud.
Think of the people who buy fancy cars and pretend they bought it for other reasons than status.
Think of those who buy modern motorcycles which have the same performance as a super car for a tiny price and an out of this world user experience.
https://news.ycombinator.com/newsguidelines.html "Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes."
Hah, I wish people who are saying 'can you even do anything with 8GB in 2026' would read posts like this.
“Big data” doesn’t have a 5gb memory cap.
I’m guessing so many devs started out on 32gb MacBooks that the NEO seems underpowered. but it wasn’t too long ago that 8gb, 1500mb/sec IO & so many cores was an elite machine.
I did a lot of dev work on a glorified eePC Chromebook when my laptop was damaged. You don’t need a lot of ram to run a terminal.
I’m hoping NEO resets the baseline testing environment so developers get back to shipping software that doesn’t monopolize resources. “Plays nice with others” should be part of the software developer’s creed.
I would have benchmarked with an instance that has local nvme, like c8gd.4xlarge.
Do they make any promises about persistence of local NVMe after something like a full-region power outage yet? Because if you can't do durable commit on a single-region cluster that will be just temporarily unavailable without loosing committed data if something like that happened, it's not quite there unless you still stream a WAL to storage that they do promise you will survive a full blackout of all zones that store (part of) the data.
Yes. They promise to wipe your data. That SLA has all the nines you can ask for as long as you measure it in the right direction :)
You already lose your data after instance restart so I think that full region outage is already out of question.
Idk how an AWS region would respond to a power outage, but i have tested this in AWS Outpost, and there, if you power down a rack, then power it back again, the baremetal instances will not be recreated. (I was surprised as I was expecting the EC2 health check to terminate them, but it does not work like that.) My understanding is that if you stop/start an instance, your local storage is gone (as the instance might even end up in a different host), but if you just reboot the instance, it should keep the local storage.
Worth noting the c8gd local NVMe is ephemeral so you'd need to pre-stage the data each run, but for a benchmark like this that's actually ideal since you avoid EBS cold-read artifacts entirely.
That's a good point. I re-ran the benchmark on two instances:
- c8gd.4xlarge - this has a single 950 GB NVMe SSD.
- c5ad.4xlarge - this has 2 x 300 GB disks, which I put in a RAID 0 array. There are no c6ad.4xlarge instances, so this is the closes NVMe-enabled approximate to ClickBench's most popular choice, c6a.4xlarge.
I also added results from my local dev machine, a MacBook M1 Max with 64 GB RAM and 10 cores.
Here are the results:
| machine | cold_run_avg | cold_run_sum | hot_run_avg | hot_run_sum |
| -------------- | -----------: | -----------: | ----------: | ----------: |
| macbook m1 max | 0.48 | 20.68 | 0.43 | 18.60 |
| macbook neo | 1.39 | 59.73 | 1.26 | 54.27 |
| c8gd.4xlarge | 0.51 | 22.04 | 0.24 | 10.36 |
| c5ad.4xlarge | 1.29 | 54.14 | 0.55 | 22.91 |
| c6a.4xlarge | 3.37 | 145.08 | 1.11 | 47.86 |
| c8g.metal-48xl | 3.95 | 169.67 | 0.10 | 4.35 |
I know this is moving the goalpost, however, it's quite interesting that both of these cloud instances with instance-attached storage are still outperformed by the M1 Max (which is 4+ years old) on the cold run. And they would quite likely lose against the latest MacBook Pro with the M5 Pro/Max on both the cold and the hot runs. But that's an experiment for another day.
> The cloud instances have network-attached disks
Props for identifying the issue immediately, but armed with that knowledge, why not redo the benchmark on a different instance type that has local storage? E.g. why not try a `c8id.2xlarge` or `c8id.4xlarge` (which bracket the `c6a.4xlarge`'s cost)?
I think it’s relevant to first read [1] to see why they’re doing this. It’s basically done as a meme.
> An alternate definition of Big Data is “when the cost of keeping data around is less than the cost of figuring out what to throw away.”
That couldn't be more accurate
Funny just yesterday I almost bought one but got cold feet and opted for a low range MacBook with M5 chip. The Apple sales rep was not convinced it would be enough when i described using it for vibecoding and deploying so kind of talked me out of getting the Neo. I normally use a mix of LLMs, then connect to Github and do a one-click deploy on CreateOS. Do you think I over-reacted? The price of the Neo is SO attractive, a clean half price compared to what I got.
Why do you need an M5 to run Cursor and a browser? Your laptop isn't doing anything in your described workflow.
I think you’ll be quite a bit happier. Between the quality of life stuff like the ancient life sensor, the pure quality stuff like a better screen and speakers, and extra RAM so it lasts longer that seems like a good decision.
The Neo is neat and for someone who mostly does surfing and standard office work kind of stuff I suspect it’s a pretty great little laptop for way less than Apple usually charges.
But it’s not going to compete with an M5 anything.
Imho 8GB RAM for productivity can quickly be restrictive. I used an M1 with 8GB and my current Macbook is M2 with 16GB, and to me the difference feels bigger than 2x. It seems not everyone here feels that way, but I'd say there's a reason Apple bumped the base models to 16 and makes that exclusive to non-Neo models.
That's not Big Data. If you "need to process Big Data on the move" - what you need is a network.
aye.
the laptop is gonna have some local code, maybe a lot, but if I'm doing legitimate "big data" that data is living i the cloud somewhere, and the laptop is just my interface.
The DuckDB team benchmarked with an r7i.16xlarge which uses EBS - that's the expected bottleneck. A fairer comparison would be an i4i or c8gd with local NVMe, where you'd likely see the laptop and cloud instance much closer in practice.
On a MacBook, one can download a data set, reboot, install updates, etc and still have the dataset. Those nice-ish AWS instances will wipe their local storage if they are stopped. Sure, one needs backups, but this is still annoying.
Also, at on-demand prices, three months of continuous usage of a single c8gd.2xlarge will pay for that MacBook Neo. The MacBook Neo has a larger SSD than the AWS instances. To be fair, the MacBook Neo has seriously nerfed external IO bandwidth, so the c8gd.2xlarge will outperform it in networking. That being said, I think that any other Mac in the current lineup will utterly smoke c8gd.2xlarge if you are willing to use Thunderbolt-connected network adapters.
Given how little power modern Macs use, a little closet full of Macs with a decent network switch will easily run on a single 20A circuit and will perform better than quite a few thousands of dollars per month of AWS products. Sadly, you’re kind of stuck on MacOS (which is not actually a fantastic server OS) and the management tools are poor. Oh, well.
I'm interested by one (not for big data) but only 8 GB or RAM is kinda really sad.
My good old LG Gram (from 2017? 2015? don't even remember) already had 24 GB of RAM. That was 10 years ago.
A decade later I cannot see myself being a laptop with 1/3rd the mem.
Did your LG Gram cost $450 (to make for $600 in today's money) in 2015-17?
If it didn't, Apple has other laptops today with more RAM.
Set up the machine yesterday. Everything runs just fine. Will use it mainly for academic writing, and light development work, only conceptual work, PoCs.
This might be a buy for me once it is fully supported by Linux. Hopefully, the muscle memory of Ctrl, Super and Alt won't get in my way.
If you can fit it on a thumb drive, it's not Big Data.
Queue the endless blog posts about running tech on the potato macbook and being stunned it’s functional with massive trade-offs. Groundbreaking stuff.
That usage is "Cue", not "queue".
Cue the queue of blogs! Trigger the formation of a line of posts to be published sequentially.
For the TPC-DS results it would also have been nice to show how the macbook neo compares to the AWS instances.
Or am I missing something?
Indeed, it would have been interesting but I really wanted to get the blog post out on the launch day of the MacBook Neo and did not have the bandwidth to run additional cloud experiments.
I ran TPC-DS SF300 now on the c6a.4xlarge. It turns out that it's still quite limited by the EBS disk's IO: while 32 GB memory is much more than 8 GB, DuckDB needs to spill to disk a lot and this shows on the runtimes. Running all 99 queries took 37 minutes, so about half of the MacBook's 79 minutes.
> Command being timed: "duckdb tpcds-sf300.db -f bench.sql"
> Percent of CPU this job got: 250%
> Elapsed (wall clock) time (h:mm:ss or m:ss): 37:00.96
> Maximum resident set size (kbytes): 25559652
> compared to 3–5 GB/s
Their numbers are a bit outdated. M5 Macbook pro SSDs are literally 5x this speed. It's wild.
I'm seeing ~6GB/sec: https://www.tomshardware.com/laptops/macbooks/m5-macbook-pro...
That's decently fast but not especially remarkable, most Gen4 NVMe drives can hit 6-7GB/sec.
To be clear, that article is about the base m5, not the m5 pro or m5 max.
https://www.apple.com/newsroom/2026/03/apple-introduces-macb...
"The new MacBook Pro delivers up to 2x faster read/write performance compared to the previous generation reaching speeds of up to 14.5GB/s..."
OP did just say M5 (implying the base model)
Those speeds on the Pro/Max are impressive though, more in line with Gen5 NVMe drives. Those have been available in desktops for some time but AFAIK the controllers are still much too hot and power hungry for laptops, so I think Apple's custom controller is actually the first to practically hit those speeds on mobile.
> TL;DR: How does the latest entry-level MacBook perform on database workloads? We benchmarked it to find out.
That's not tldr, that's just subheader.
Thank you! I was going to say the same thing. It doesn’t give mr an overview at all
That c8g.metal-48xl instance costs $7.63008 on demand[1], so for the price of the laptop, you could run queries on it for about ~90 hours.
:shrug: as to whether that makes the laptop or the giant instance the better place to do one's work…
this has a phone CPU/memory
other test:
2025-09-08 : "Big Data on the Move: DuckDB on the Framework Laptop 13"
"TL;DR: We put DuckDB through its paces on a 12-core ultrabook with 128 GB RAM, running TPC-H queries up to SF10,000."
https://duckdb.org/2025/09/08/duckdb-on-the-framework-laptop...
[dead]
[dead]
[dead]
[flagged]
[flagged]
[flagged]
[flagged]
> And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
That’s because battery life was pretty mediocre across the board, with Apple occasionally squeaking out a bit of an upper hand on the Air. Most laptops were in the same boat, aside from gaming and workstation laptops but battery life has never been the point of those.
That changed dramatically with the M-series Macs. People didn’t start caring because Apple did, but because it meant no longer being tethered to a wall, being able to do a lot of outings without a brick or charger cable at all, and on extended trips being able to get by with a little phone charger instead of a the usual huge ungainly brick.
One of the primary objectives of a laptop is portability, and long battery life is an objective upgrade in that category. Not everybody needs it but for those who do it’s difficult to give up once you’ve had it.
EDIT: Another advantage of that higher efficiency is that MacBooks can run at full performance without being plugged in without it obliterating battery life. x86 laptops universally throttle when untethered and while this can be disabled, they burn through their batteries much more quickly.
I don't think anyone that dismisses this really understands this. I've never had a laptop that could for more than about 3-4 hours doing dev work, but in 2014 I could get 8 hours of dev time out of an Air, and I can do that now on my M1 Macbook Pro.
For someone who is actually out and about all the time, this is life changing.
If you just sit with your laptop tethered at your desk all day, they why would you ever care?
To be honest I never had Issues with Battery Life on my ThinkPad. I've gotten out 10-12 hours with the 96Wh Battery and never felt the need for much more.
I think most people who are so wowed by Macs bought just a garbage Windows Machine (e.g. almost everything from Asus and Acer) before and then splurged the money for a nice one, so obviously it's so much better in comparison.
Is that under Windows or Linux? It’s not awful, but depending on usage a MacBook can do 16h+ with the same size battery, especially if put into low power mode, which is substantially better.
The smaller 13” Air also gets similar numbers despite its smaller battery, which is a big deal for people who don’t want to lug around a 15/16” laptop.
Maybe it's an excellent experience these days, but every time I've tried Linux on desktop over the past 25 years I get burned. Maybe it works for a while, then your NIC driver gets borked and you spend 2 days trying to get it working again. Or some update goes sideways and you lose the GUI, launching only into a terminal. It's always something. And laptops have even less common hardware than desktops.
On the other hand, every Mac I've used over the past 15 years has been bulletproof. It turns on, it works, it runs *nix. It's an invisible interface to getting work done.
FWIW I have had no issues on a thinkpad for past 10 years running standard linux distros. I think it may come down to a combo of os and particular mb/laptop which is pretty easy to find recommendations.
I'd be willing to gamble that you used Debian-family. Debian is outdated linux. It is literally designed to be 2 years outdated upon release.
Use Fedora. Its up to date.
Note that Fedora is NOT Arch.
That's kinda the point of the Mac though, you don't have to get the right distribution or deal with pedantry, you buy, take it home, open it and will run for 8-10 hours of work without charging. No distro issues.
But then you dont get Nvidia, 16gb, or 512 SSD.
And all you needed to do was know Fedora is SOTA. Once you know that, you don't need to change.
> And I have a hard time believing people who tell me stories about low power consumption, because no one had cared about that until Apple pretended people cared about it.
I haven't packed a charger for the day for 3 years. I can work in coffee shops or on the couch for over 6 hours without even thinking about charging. I'm sorry but if you haven't tried the M* macbooks you don't know what you're criticising.
You get a long-lasting device that's usually pleasant to use. User experience is harder to measure than specs, but at least for me, Macbooks are consistently better laptops than everything else I've used.
People care about how long you can run in between charging. Low power consumption helps with that, even if you don't care about it directly.
Yeah, but then MacBook is going to run smoother and faster than the Windows one (and I don’t want to spend even one extra minute on dealing with drivers on Linux). There’re just objective benchmarks for that.
And MacBooks also have a better display and build quality. Like, touchpad is still hit or miss on any non-Apple device.
My work laptop is a common HP model from just a few years ago.
The screen is seriously ‘meh’, a massive upgrade from the previous HP model’s “you paid how much for this?”
Both have plastic cases that are fine but don’t feel tight/solid.
The keyboards are 80% and off center so there’s a numpad, which makes things hard to type for me.
The trackpads are fine. Which is way better than I was expecting.
Neither held a candle in speed or quality to my 16 GB M1 Air, and they are developer laptops, not $600 models.
I’m pretty sure I’d want a Neo over a $600 PC for non-developer work.
And the noise. Spin the fan up. Now down. Now up. Now down. Random spinning HD noises too (2nd disk I don’t use). Just to sit on the desktop.
People want a laptop that has
- Great battery life
- Solid build quality
- A familiar interface (iPhone is the most popular OS in the US)
- Good enough speed and snappiness for the tasks they can't do on their phone
- Can walk into Costco or buy online at Amazon without having to hunt for deals or refurbs
- Is from a brand they are familiar with and has an association with quality.
- Is somewhere around $500-$800, the most common price range for laptops today
The MacBook Neo ticks all those boxes, and it comes in fun colors. It's the one you can walk into a store, buy, not really sweat the speeds and feeds and know you will have a pretty great experience with. I'm not sure why so many people are having a hard time understanding this.
Where do I get a Laptop with a Nvidia GPU for 600$ ?
I'm right now in the Market for a new Laptop, because I need way more GPU Power than my T470 provides, and to be honest the MacBookPros are quite competitively priced compared to the P-ThinkPads with Nvidia Cards. (Both around 3000€) They also finally offer a matte screen option
The only thing holding me back right now is the soldered SSD, RAM (and shitty Linux support).
It was quite nice being able to upgrade RAM, SSD and replace the Battery on it. Otherwise it wouldn't have lasted for 9 years
> You could get a laptop with an Nvidia GPU, 16gb ram, 512 ssd... or a 'cheap' Macbook.
That laptop won't have half the battery life the macbook does. It really all only boils down to the "handiness" of the device.
[flagged]
[flagged]
Did you use AI to write a one-paragraph comment?
> MacBook Neo's NVMe being slower than the Air/Pro isn't just a benchmark footnote — it compounds with file count in a non-linear way.
The “isn’t just” part is a dead giveaway almost always.
It's probably worse than that - he probably used AI to look for things to comment on and automatically create comments. He's not even here.
it really is the stereotypical form of "it's not just this, it's actually that", and even an em-dash!
[flagged]
Your comment is fully AI generated which is against HN guidelines https://www.pangram.com/history/6e9e9161-73d8-4860-88cf-2424...
> Don't post generated comments or AI-edited comments. HN is for conversation between humans.
Would it not also work on a raspberry.
With I/O streaming and efficient transformation I do big data on my consumer PC and good old cheap HDDs just fine.
I suspect the Neo’s A-series chip wipes the floor with a Pi.
I’m really surprised just how competitive it was in their benchmark. I was expecting “sure it doesn’t compete but it works and you can use it”, not “it beat an Amazon instance, though not a really powerful one”.
IO on a raspi is pathetic. As packaged it’s 100 times slower , with a M.2 hat it’s still 5x slower
Oh great, the term "big data" is back.
So my definition of big data was data so big it cannot be processed on a single machine in a reasonable amount of time.
I guess they’re using a different definition?
I think it's partly tongue in cheek, because when "big data" was over hyped, everyone claimed they were working with big data, or tried to sell expensive solutions for working with big data, and some reasonable minds spoke up and pointed out that a standard laptop could process more "big data" than people thought.
> For our first experiment, we used ClickBench, an analytical database benchmark. ClickBench has 43 queries that focus on aggregation and filtering operations. The operations run on a single wide table with 100M rows, which uses about 14 GB when serialized to Parquet and 75 GB when stored in CSV format.
very much so…
In my former life as a soulless consultant mid-level IT managers really liked to hear the 3 "V"s mentioned: Velocity, Volume, Variety
Computers got bigger and software got smarter.
You have phones that are faster than cloud VMs of the past. You can use bare metal servers with up to 344 cores and 16TB of ram.
I used to share your definition too, but I now say that if it doesn’t open in Microsoft Excel, it’s big data.
Processing data that cannot be processed on a single machine is fundamentally a different problem than processing data that can be processed on a single machine. It's useful to have a term for that.
As you say, single machines can scale up incredibly far. That just means 16 TB datasets no longer demand big data solutions.
I get your point, but I don’t know if big data is the right term anymore.
Many people like to think they have big data, and you kinda have to agree with them if you want their money. At least in consulting.
Also you could go well beyond a 16TB dataset on a single machine. You assume that the whole uncompressed dataset has to fit in memory, but many workloads don’t need that.
How many people in the world have such big datasets to analyse within reasonable time?
Some people say extreme data.
“Your data isn’t big” is a good working definition of big data.
Google has big data. You are not google.
I think the definition of big is smaller than that. Mine was "too big to fit on a maxed-out laptop", effectively >8TB. Our photo collection is bigger than that, it's not 'big data'.
Or one could define it as too big to fit on a single SSD/HDD, maybe >30TB. Still within the reach of a hobbyist, but too large to process in memory and needs special tools to work with. It doesn't have to be petabyte scale to need 'big data' tooling.
“Your data is not big” comes from this thread…https://news.ycombinator.com/item?id=7192839
8TB is a couple hundred hours of 4k RAW video assets.
Seems completely unnecessary, there is probably 0 overlap between people who buy a cheap MacBook and people running DuckDB locally
I agree I don’t think it’s going to be something people really do.
I just thought it was neat. It’s a phone chip, we’ve never been able to do stuff like this on an Apple phone chip before. No one was porting this to the iPhone to run there.
In my mind this is purely a curiosity article, and I like that.
You'd be surprised. There are many of us analysts in the third world who are paid pennies and expected to build large-scale exec dashboards from nontrivial data - with no cloud support whatsoever. ETL has to be local from hundreds of GBs of csv dumps.
I've used MacBook Airs as primary dev machines multiple times in my career (before Apple silicon, when Airs had truly shit performance).
There is always a trade-off of cost/convenience/power, and some folks are going to end up the the Neo end of the spectrum.
I love small form factors, and I am what youd call a professionel :P
I think the form factor is basically the same (maybe slightly thicker) as a Macbook Air. It's basically an Air with lower performance in most dimensions.
It’s necessary because the ignorant keep saying 8GB of RAM is a deal breaking limitation on the cheapest MacBook available.
Mind blown, if you need to handle "big" data on the move - the macbook neo is not the right choice. - Who would have guessed that outcome?
It occurs to me that there is near zero overlap between people who use a Macbook Neo and people who run DuckDB locally.
It would be a surprise if more than 0.1% of Macbook Neo users have even heard of DuckDB.
Which means that this article is probably just riding the hype.
Trying DuckDB on lower-end Macbooks does show you dont need much muscle for moderate-size analytics. Long term it isnt cost-effective compared to budget laptops but its super simple for self-contained pipelines. The thing is 8GB RAM leaves you stuck once your data actually grows past the marketing demo.
I think you completely missed the point.
People buy Macbook Neo because they "just need a laptop" or are budget conscious.
I imagine a student would get their hands wet with Postgre before looking at DuckDB or similar.
It would be a surprise if they do heavy workloads with DuckDB. In which case it's definitely worth investing in a more powerful computer.
Doesn’t matter. The point is that DuckDB can operate well on a wide range of infrastructure and is well suited for operating in resource constrained environments.
That's an awesome idea to get a bricked MacBook Neo really fast because those idiots soldered the SSD inside
Apple has been soldering the SSD into MacBooks for over 10 years now, and most 10 year old MacBooks still have a working SSD.
Not if you're powerusing it like in the Article and relying heavily on Swap.
Also there are countless reports of bricked M1 8GB MacBook Airs that are bricked because the SSD used up it's write cycles
That's not what the video insinuates.
Yes you're right. I meaned a different video, but I can't find it right now. I've looked it up, and back then MacOS had a bug which exacerbated that issue. Here is an article
https://www.macrumors.com/2021/02/23/m1-mac-users-report-exc...
You originally stated "Also there are countless reports of bricked M1 8GB MacBook Airs that are bricked because the SSD used up it's write cycles"
Do you have a source for these "countless bricked SSD's"?
Here was the Video I meant back then.
https://m.youtube.com/watch?v=MZuv4TIjk-I&pp=ygURZGVhZCBNYWN...
Not sure about the ssd in particular but the neo is apparently pretty modular
Fantastic tear down. Thank you. Amazing for Apple. I hope this is the trend going forward but probably not. But still a gazillion screws? I just replaced the keyboard for my old hp elitebook with two screws.
I don't care about a gazillion screws, if it's serviceable in the End.
If Apple would build their laptops serviceable like ThinkPads I would buy one today.
It seems like they’re starting to learn the cost of being too integrated.
They’ve slowly been moving towards making it easier to repair individual broken parts. I’m very happy to see that a new keyboard doesn’t require replacing the entire top case. That was just crazy.
>Can I expect good performance from the MacBook Neo with Slack, Microsoft Office, and Google Chrome signed into Atlassian and a CRM, all running simultaneously?
No.
>Do I reject a world where all of the above is necessary to realize value from an entry-level MacBook?
In theory, yes.