Summarizer

People are slow to realize the benefit of immutable databases, but it is happening. It's not just auditability; immutable databases can also allow concurrent reads while writes are happening, fast cloning of data structures, and fast undo of transactions. The ones you mentioned are large backend databases, but I'm working on an "immutable SQLite"...a single file immutable database that is embedded and works as a library: https://github.com/radarroark/xitdb-java

From my perspective on databases, two trends continued in 2025: 1: Moving everything to SQLite 2: Using mostly JSON fields Both started already a few years back and accelerated in 2025. SQLite is just so nice and easy to deal with, with its no-daemon, one-file-per-db and one-type-per value approach. And the JSON arrow functions make it a pleasure to work with flexible JSON data.

From my perspective - do you even need a database? SQLite is kind-of the middle ground between a full fat database, and 'writing your own object storage'. To put it another way, it provides 'regularised' object access API, rather than, say, a variant of types in a vector that you use filter or map over.

If I would write my own data storage I would re-implement SQLite. Why would I want to do that?

Not sure if this is quite what you are getting at, but the SQLite folks even mention this as a great use-case: https://www.sqlite.org/appfileformat.html

As a backend database that's not multi user, how many web connections that do writes can it realistically handle? Assuming writes are small say 100+ rows each? Any mitigation strategy for larger use cases? Thanks in advance!

Couple thousand simultaneous should be fine, depending on total system load, whether you're running on spinning disks or on SSDs, p50/99 latency demands and of course you'd need to enable the WAL pragma to allow simultaneous writes in the first place. Run an experiment to be sure about your specific situation.

You also need BEGIN CONCURRENT to allow simultaneous write transactions. https://www.sqlite.org/src/doc/begin-concurrent/doc/begin_co...

After 2 years in production with a small (but write heavy) web service... it's a mixed bag. It definitely does the job, but not having a DB server does have not only benefits, but also drawbacks. The biggest being (lack of) caching the file/DB in RAM. As a result I have to do my own read caching, which is fine in Rust using the mokka caching library, but it's still something you have to do yourself, which would otherwise come for free with Postgres. This of course also makes it impossible to share the cache between instances, doing so would require employing redis/memcached at which point it would be better to use Postgres. It has been OK so far, but definitely I will have to migrate to Postgres at one point, rather sooner than later.

As I said, my app is write heavy. So there are several separate processes that constantly write to the database, but of course, often, before writing, they need to read in order to decide what/where to write. Currently they need to have their own read cache in order to not clog the database. The "web service" is only the user facing part which bears the least load. Read caching is useful there too as users look at statistics, so calculating them once every 5-10 minutes and caching them is needed, as that requires scanning the whole database. A CDN is something I don't even have. It's not needed for the amount of users I have. If I was using Postgres, these writer processes + the web service would share the same read cache for free (coming from Posgres itself). The difference wouldn't be huge if I would migrate right now, but now I already have the custom caching.

I am no expert, but SQLite does have in memory store? At least for tables that need it..ofc sync of the writes to this store may need more work.

Why have multiple connections in the first place? If your writes are fast, doing them serially does not cause anyone to wait. How often does the typical user write to the DB? Often it is like once per day or so (for example on hacker news). Say the write takes 1/1000s. Then you can serve 1000 * 60 * 60 * 24 = 86 million users And nobody has to wait longer than a second when they hit the "reply" button, as I do now ...

> If your writes are fast, doing them serially does not cause anyone to wait. Why impose such a limitation on your system when you don't have to by using some other database actually designed for multi user systems (Postgres, MySQL, etc)?

Because development and maintenance faster and easier to reason about. Increasing the chances you really get to 86 million daily active users.

So in this solution, you run the backend on a single node that reads/writes from an SQLite file, and that is the entire system?

Thats basically how the web started. You can serve a ridiculous number of users from a single physical machine. It isn't until you get into the hundreds-of-millions of users ballpark where you need to actually create architecture. The "cloud" lets you rent a small part of a physical machine, so it actually feels like you need more machines than you do. But a modern server? Easily 16-32+ cores, 128+gb of ram, and hundreds of tb of space. All for less than 2k per month (amortized). Yeah, you need an actual (small) team of people to manage that; but that will get you so far that it is utterly ridiculous. Assuming you can accept 99% uptime (that's ~3 days a year being down), and if you were on a single cloud in 2025; that's basically last year.

I agree...there is scale and then there is scale. And then there is scale like Facebook. We need not assume internet FB level scale for typical biz apps where one instance may support a few hundred users max. Or even few thousand. Over engineering under such assumptions is likely cost ineffective and may even increase surface area of risk. $0.02

That depends on the use case. HN is not a good example. I am referring to business applications where users submit data. Ofc in these cases we are looking at 00s not millions of users. The answer is good enough.

Pardon my ignorance, yet wasn't the prevailing thought a few years ago that you would never use SQLite in production? Has that school of thought changed?

SQlite as a database for web services had a little bit of a boom due to: 1. People gaining newfound appreciation of having the database on the same machine as the web server itself. The latency gains can be substantial and obviously there are some small cost savings too as you don't need a separate database server anymore. This does obviously limit you to a single web server, but single machines can have tons of cores and serve tens of thousands of requests per second, so that is not as limiting as you'd think. 2. Tools like litestream will continuously back up all writes to object storage, so that one web server having a hardware failure is not a problem as long as your SLA allow downtimes of a few minutes every few years. (and let's be real, most small companies for which this would be a good architecture don't have any SLA at all) 3. SQLite has concurrent writes now, so it's gotten much more performant in situations with multiple users at the same time. So for specific use cases it can be a nice setup because you don't feel the downsides (yet) but you do get better latency and simpler architecture. That said, there's a reason the standard became the standard, so unless you have a very specific reason to choose this I'd recommend the "normal" multitier architectures in like 99% of cases.

> SQLite has concurrent writes now Just to clarify: Unless I've missed something, this is only with WAL mode and concurrent reads at the same time as writes, I don't think it can handle multiple concurrent writes at the same time?

I think only Turso — SQLite rewritten in Rust — supports that.

I’m a fan of SQLite but just want to point out there’s no reason you can’t have Postgres or some other rdbms on the same machine as the webserver too. It’s just another program running in the background bound to a port similar to the web server itself.

SQLite is likely the most widely used production database due to its widespread usage in desktop and mobile software, and SQLite databases being a Library of Congress "sustainable format".

Most of the usage was/is as a local ACID-compliant replacement for txt/ini/custom local/bundled files though.

"Production" can mean many different things to different people. It's very widely used as a backend strutured file format in Android and iOS/macOS (e.g. for appls like Notes, Photos). Is that "production"? It's not widely used and largely inappropriate for applications with many concurrent writes. Sqlite docs has a good overview of appropriate and inappropriate uses: https://sqlite.org/whentouse.html It's best to start with Section 2 "Situations Where A Client/Server RDBMS May Work Better"

Only for large scale multiple user applications. It’s more than reasonable as a data store in local applications or at smaller scales where having the application and data layer on the same machine are acceptable. If you’re at a point where the application needs to talk over a network to your database then that’s a reasonable heuristic that you should use a different DB. I personally wouldn’t trust my data to NFS.

This, though I think other posters have pointed to a web app/site that’s backed by SQLite. It can be a perfectly reasonable approach, I think, as the application is the web server and it likely accesses SQLite on the same machine.

The reason you heard that was probably because they were talking about a more specific circumstance. For example SQLite is often used as a database during development in Django projects but not usually in production (there are exceptions of course!). So you may have read when setting up Django, or a similar thing, that the SQLite option wasn't meant for production because usually you'd use a database like Postgres for that. Absolutely doesn't mean that SQLite isn't used in production, it's just used for different things.

I would say SQLite when possible, PostgreSQL (incl. extensions) when necessary, DuckDB for local/hobbyist data analysis and BigQuery (often TB or PB range) for enterprise business intelligence.

I think the right pattern here is edge sharding of user data. Cloudflare makes this pretty easy with D1/Hyperdrive.

For as much talk as I see about SQLite, are people actually using it or does it just have good marketers?

Among people who can actually code (in contrast to just stitch together services), I see it used all around. For someone who openly describes his stack and revenue, look up Pieter Levels, how he serves hundreds of thousands of users and makes millions of dollars per year, using SQLite as the storage layer.

It's the standard for mobile. That said, in server-side enterprise computing, I know no one who uses it. I'm sure there are applications, but in this domain you'd need a good justification for not following standard patterns. I have used DuckDB on an application server because it computes aggregations lightning fast which saved this app from needing caching, background services and all the invalidation and failure modes that come with those two.

> are people actually using it or does it just have good marketers? _You_ are using it right this second. It's storing your browser's bookmarks (at a minimum, and possibly other browser-internal data).

If you use desktops, laptops, or mobile phones, there is a very good chance you have at least ten SQLite databases in your possession right now.

It is fantastic software, have you ever used it?

I don't have a use case for it. I've used it a tiny bit for mocking databases in memory, but because it's not fully Postgres, I've switched entirely to TestContainers.

I can't believe that article has no mention of SQLite ??

> I can't believe that article has no mention of SQLite ?? https://www.cs.cmu.edu/~pavlo/blog/2026/01/2025-databases-re...

No MSSQL, DB2 or Oracle either. Anything this proven & stable is probably not worth blogging about in this context. SQLite gets a lot of attention on HN but that's a bit of an exception.

Same. CMD-F, 'sqlite', no hits, skip and go straight to comments.

Why does "database" is surveys like this not include DuckDB and SQLite, which are great [1] embedded answers to Clickhouse and PostgreSQL. Both are excellent and useful databases; DuckDB's reasonable syntax, fast vectorized everything, and support for ingesting the hairiest of data as in-DB ETL make me reach for it first these days, at least for the things I want to do. Why is it that in "I'm a serious database person" circles, the popular embedded databases don't count? [1] Yes, I know it's not an exact comparison.