As someone with TBs of SSDs and HDDs laying around I am someone who agrees with your point, but this is not a good way to compare costs.
For one, this has no redundancy and doesn't factor the cost of the machine providing the storage. But also it's an upfront cost for storing 4TB. It would be implied you wouldn't literally store 4TB on the SSD because now you're out of capacity for more data. If you only have 2GB of data in a bucket then S3 is still magnitudes cheaper, faster, and more redundant than anything you could put together yourself because the cost is spread across all the users of the service.
Reality is there are so many times that S3 makes the most sense that it makes people short-circuit and always pick S3 despite the huge hidden IOPS and bandwidth costs everyone rightfully tries to point out.
It's not "cheap". 6 months of S3 is at around price of outright buying 4TB SSD at retail price. That before you do any IOPS to it
This is badly misunderstanding the problem: S3 is a highly available service with geographic redundancy and a huge range of integrated features. Your comparison would need to be updated to include multiple running servers in addition to redundant storage, and the software stack implementing things like immutability, not to mention all of the security features.
That’s not to say that you can’t build equivalents for the parts you use but you either need massive scale or giving up features to do that. For example, if you can tolerate bitrot or long access times if hardware fails, you can definitely get a lower cost per terabyte.
The reason why most people don’t do that, even when they have scale, is that it adds cost and risk everywhere else if you need engineering/ops people working on storage. If you’re, say, the internet archive that might make sense—it’s quite literally why your organization exists—but most other places are going to see all of the integrated features that they don’t have to build and operate paying for the difference between S3 and physical media pricing. For example, if I want to process files as soon as they’re uploaded or have immutability, I can just turn that on rather than having to build more services.
Try doing the math and ask why your time costs. You need to buy a lot of storage to pay for the engineering work and most places would prefer to spend that time and attention on the product rather than shaving a few percent off of the storage bill (especially since the savings will be negative for quite some time).
Wait, I'm confused, are you arguing for or against S3? Did you mean factoring the time needed to obtain the multiple PhD levels of information in tracking the cost, usage, and security of those interoperable services plugged into S3?
I have done the math as part of my job and often found that yes, it was literally worth the money to do our own storage in cases. Running a highly available, durable storage system is not particularly difficult. There was an era when it was a common skill for a sysadmin. In the current era there are off the shelf solutions for it, both open and proprietary.
The biggest reason people pay for S3 is because of data transfer cost to other cloud services they are using.
Of course, if you had paid extra for the backups and redundancy, your data would survive.
So to address your original point, unless you are paying extra for redundancy, it is cheaper if you use a 4TB SSD at retail price as the original commenter discussed.
If you play the game correctly it can be a good deal. The ~1 USD per TB per month of glacier deep archive is hard to compete with if you (probably) don’t need to read the data back.
Nice article. I agree that it is a bit of a shame that everything is forced to be so S3-centric (and I say that as someone whose work helped motivate a lot of people to do that), but right now its an unfortunate reality of running software in the cloud because cloud networking and SSDs are so expensive that you really are required to use S3 if you want a system that can handle "big data" scale workloads cost effectively
The unfortunate part of that graph is that I think it's not updated for today's prices given the memory shortage/crunch we're experiencing that's driven up the prices for all kinds of memory.
But also while it should be faster than it is, how would an S3 designed around SSDs look differently to an API user? I would think the API is basically the same.
We ran EBS for years. Finally the costs became ridiculous and we moved our entire dataset to S3. We’re saving 20k/month. There’s just no beating the price.
That's true for the base S3 product, but there are a lot more storage tiers than there used to be with cheaper pricing. All the way to $0.99/TB for Deep Archive.
Egress pricing of $0.09/GB has been around for over a decade too.
For reference transit cost has dropped over the years and is now about at $0.000247/GB or free if there is a peering agreement with the network the data is sent to.
Right now it is not even clear how to interface with SSDs even on a single host, there has been all sorts of attempts to move away from the traditional plain block device model. NVMe has extensions for KV, ZNS, and FDP, all which offer different characteristics. And then there are of course open channel SSDs and some others too. I kinda expect the future foundational IO interface to be more S3-like than block-device or unixy filesystem-like.
I really wish reviewers would harp on FDP (Flexible Data Placement) and perhaps KV support. FDP supposedly somewhat ate ZNS as a spec, allegedly, but there might be gaps, reasons to keep ZNS.
There's only a small little mention, if we are lucky, on the couple drives that have it (expensive enterprise flagships). It should be a regular sticking point, whether it's there or not. Without pressure it's not going to get regularly available, it feels like.
FDP is so simple. Declare a number for what pool of data you want to write into. Data of the same pool gets written to the same storage such that you can wipe it latter together. It has huge wins though against write amplification! Massive wins. For so close to free.
The NVMe-KV is more radical. Still worth putting some pressure on, but your drive as KV, as object store, feels harder. Side note, really enjoyed this ceph nvme-kv offload post thing, my favorite tech write up in a while! https://ceph.io/en/news/blog/2026/for-whom-the-door-bell-tol...
I find Cloudflare R2 to be much cheaper as there are zero egress fees irrespective of data size. One is only billed on the count of requests with 10 million free download requests per month (check pricing for precise info).
If you do a clever bit of caching work in your app like we have with our apps Slyp and SlypBusiness, you could even make it insanely cheap.
We have a file manager that is ultimately responsible for images, files, videos and whatnot. It loads the images/files from the downloaded local cache when requested by a feature in the app.
A standard feature uploads and downloads using signed urls obtained from the backend service. The manager increments the file's version in the backend on each successful upload. For download, the manager compares the version against the locally cached version. If there is an update, the new file is downloaded in the background and overwrites the local cache and notifies all features using the file inside the app.
It's not "cheap". 6 months of S3 is at around price of outright buying 4TB SSD at retail price. That before you do any IOPS to it
S3 is terrible deal on any front. it's just easy
Everything in AWS is expensive. But at least S3 adds a lot of value.
As someone with TBs of SSDs and HDDs laying around I am someone who agrees with your point, but this is not a good way to compare costs.
For one, this has no redundancy and doesn't factor the cost of the machine providing the storage. But also it's an upfront cost for storing 4TB. It would be implied you wouldn't literally store 4TB on the SSD because now you're out of capacity for more data. If you only have 2GB of data in a bucket then S3 is still magnitudes cheaper, faster, and more redundant than anything you could put together yourself because the cost is spread across all the users of the service.
Reality is there are so many times that S3 makes the most sense that it makes people short-circuit and always pick S3 despite the huge hidden IOPS and bandwidth costs everyone rightfully tries to point out.
This is badly misunderstanding the problem: S3 is a highly available service with geographic redundancy and a huge range of integrated features. Your comparison would need to be updated to include multiple running servers in addition to redundant storage, and the software stack implementing things like immutability, not to mention all of the security features.
That’s not to say that you can’t build equivalents for the parts you use but you either need massive scale or giving up features to do that. For example, if you can tolerate bitrot or long access times if hardware fails, you can definitely get a lower cost per terabyte.
The reason why most people don’t do that, even when they have scale, is that it adds cost and risk everywhere else if you need engineering/ops people working on storage. If you’re, say, the internet archive that might make sense—it’s quite literally why your organization exists—but most other places are going to see all of the integrated features that they don’t have to build and operate paying for the difference between S3 and physical media pricing. For example, if I want to process files as soon as they’re uploaded or have immutability, I can just turn that on rather than having to build more services.
Even if you factor that it, S3 is pretty expensive for most small to medium size data.
Try doing the math and ask why your time costs. You need to buy a lot of storage to pay for the engineering work and most places would prefer to spend that time and attention on the product rather than shaving a few percent off of the storage bill (especially since the savings will be negative for quite some time).
Wait, I'm confused, are you arguing for or against S3? Did you mean factoring the time needed to obtain the multiple PhD levels of information in tracking the cost, usage, and security of those interoperable services plugged into S3?
Many of us just dont buy your argument. "Engineering work" for maintaining our own storage is not rocket science.
You just plug it in and basically it runs. Thats pretty much it.
I have done the math as part of my job and often found that yes, it was literally worth the money to do our own storage in cases. Running a highly available, durable storage system is not particularly difficult. There was an era when it was a common skill for a sysadmin. In the current era there are off the shelf solutions for it, both open and proprietary.
The biggest reason people pay for S3 is because of data transfer cost to other cloud services they are using.
Recent Iranian attacks on AWS locations in Bahrain resulted in loss of data that simply could not be recovered. https://www.infoq.com/news/2026/09/aws-middle-east-data-loss...
Of course, if you had paid extra for the backups and redundancy, your data would survive.
So to address your original point, unless you are paying extra for redundancy, it is cheaper if you use a 4TB SSD at retail price as the original commenter discussed.
If you play the game correctly it can be a good deal. The ~1 USD per TB per month of glacier deep archive is hard to compete with if you (probably) don’t need to read the data back.
Nice article. I agree that it is a bit of a shame that everything is forced to be so S3-centric (and I say that as someone whose work helped motivate a lot of people to do that), but right now its an unfortunate reality of running software in the cloud because cloud networking and SSDs are so expensive that you really are required to use S3 if you want a system that can handle "big data" scale workloads cost effectively
The unfortunate part of that graph is that I think it's not updated for today's prices given the memory shortage/crunch we're experiencing that's driven up the prices for all kinds of memory.
But also while it should be faster than it is, how would an S3 designed around SSDs look differently to an API user? I would think the API is basically the same.
It would probably look a lot like existing S3 concepts that have explicit hot and cold tiers. For example Intelligent Tiering, or Glacier.
That's S3 Express One Zone. Directory buckets are SSD-backed and regular buckets are HDD-backed. Some of the API differences off the top of my head:
- Directory entries are no longer returned in sorted order in ListObjectsV2
- There's an AppendObject API
- There's a RenameObject API
We ran EBS for years. Finally the costs became ridiculous and we moved our entire dataset to S3. We’re saving 20k/month. There’s just no beating the price.
One thing I find notable about S3 today is that, while it used to drop in price reasonably often, there hasn't been a price drop in a full decade:
Today it's still $0.023/GB-month.
That's true for the base S3 product, but there are a lot more storage tiers than there used to be with cheaper pricing. All the way to $0.99/TB for Deep Archive.
Well there was also a period of low inflation in them during that time.
God why am I defending Amazon?
Not that deep archive isn't a valid option for the appropriate work load, but it has different effective costs.
Egress pricing of $0.09/GB has been around for over a decade too.
For reference transit cost has dropped over the years and is now about at $0.000247/GB or free if there is a peering agreement with the network the data is sent to.
I guess inflation is the price reduction we get. 23 cents in 2016 is 32 cents in 2026
Right now it is not even clear how to interface with SSDs even on a single host, there has been all sorts of attempts to move away from the traditional plain block device model. NVMe has extensions for KV, ZNS, and FDP, all which offer different characteristics. And then there are of course open channel SSDs and some others too. I kinda expect the future foundational IO interface to be more S3-like than block-device or unixy filesystem-like.
I really wish reviewers would harp on FDP (Flexible Data Placement) and perhaps KV support. FDP supposedly somewhat ate ZNS as a spec, allegedly, but there might be gaps, reasons to keep ZNS.
There's only a small little mention, if we are lucky, on the couple drives that have it (expensive enterprise flagships). It should be a regular sticking point, whether it's there or not. Without pressure it's not going to get regularly available, it feels like.
FDP is so simple. Declare a number for what pool of data you want to write into. Data of the same pool gets written to the same storage such that you can wipe it latter together. It has huge wins though against write amplification! Massive wins. For so close to free.
Some day I want to own a FDP drive. And then I can finally start using the tokio/io-uring support that I contributed! https://github.com/tokio-rs/io-uring/issues/380
The NVMe-KV is more radical. Still worth putting some pressure on, but your drive as KV, as object store, feels harder. Side note, really enjoyed this ceph nvme-kv offload post thing, my favorite tech write up in a while! https://ceph.io/en/news/blog/2026/for-whom-the-door-bell-tol...
I find Cloudflare R2 to be much cheaper as there are zero egress fees irrespective of data size. One is only billed on the count of requests with 10 million free download requests per month (check pricing for precise info).
If you do a clever bit of caching work in your app like we have with our apps Slyp and SlypBusiness, you could even make it insanely cheap.
We have a file manager that is ultimately responsible for images, files, videos and whatnot. It loads the images/files from the downloaded local cache when requested by a feature in the app.
A standard feature uploads and downloads using signed urls obtained from the backend service. The manager increments the file's version in the backend on each successful upload. For download, the manager compares the version against the locally cached version. If there is an update, the new file is downloaded in the background and overwrites the local cache and notifies all features using the file inside the app.