Databases in 2025: A Year in Review

Popularity can mean multiple things. Are we talking about how frequently a database is used or how frequently a database is chosen for new projects? MySQL will always be very popular because some very popular things use it like WordPress.

It does feel like a lot of the momentum has shifted to PostgreSQL recently. You even see it in terms of what companies are choosing for compatibility. Google has a lot more MySQL work historically, but when they created a compatibility interface for Cloud Spanner, they went with PostgreSQL. ClickHouse went with PostgreSQL. More that I'm forgetting at the moment. It used to be that everyone tried for MySQL wire compatibility, but that doesn't feel like what's happening now.

If MySQL is making you happy, great. But there has certainly been a shift toward PostgreSQL. MySQL will continue to be one of the most used databases just as PHP will remain one of the most used programming languages. There's a lot of stuff already built with those things. I think most metrics would say that PHP is more widely deployed than NodeJS, but I think it'd be hard to argue that PHP is what the developer community is excited about.

Even search here on HN. In the past year, 4 MySQL stories with over 100 point compared to 28 PostgreSQL stories with over 100 points (and zero MariaDB stories above 100 points and 42 SQLite). What are we talking about here on HN? Not nearly as frequently MySQL - we're talking about SQLite and PostgreSQL. That's not to say that MySQL doesn't work great for you or that it doesn't have a large installed base, but it isn't where our mindshare is about the future.

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.

> There are rumblings that the MySQL project is rudderless after Oracle fired the team working on the open-source project in September 2025.

Not just the open-source project; 80%+ (depending a bit on when you start counting) of the MySQL team as a whole was let go, and the SVP in charge of MySQL was, eh, “moving to another part of the org to spend more time with his family”. There was never really a separate “MySQL Community Edition team” that you could fire, although of course there were teams that worked mostly or entirely on projects that were not open-sourced.

What an amazing set of articles, one thing that I think he's missed is the clear multi year trends.

Over the past 5 years there's been significant changes and several clear winners. Databricks and Snowflake have really demonstrated ability to stay resilient despite strong competition from cloud providers themselves, often through the privatization of what previously was open source. This is especially relevant given also the articles mentioning of how cloudera and hortonworks failed to make it.

I also think the quiet execution of databases like clickhouse have shown to be extremely impressive and have filled a niche that wasn't previously filled by an obvious solution.

> the question (in my mind) is balancing the length of that delay with the usefulness of column order queries for a given workload. I seem to keep running into workloads that do inserts very quickly and then batch reads on a slower cadence (either in lockstep with the writes, or concurrently) but not on the extremely slow cadence seen in the typical olap reporting type flow. Essentially, building up state and then querying the results.

I see. Can you come up with row/table watermarks? Say your column store is up-to-date with certain watermark, so any query that requires freshness beyond that will need to snoop into the rows that haven't made it into the columnar store to check for data up to the required query timestamp.

In the past I've dealt with a system that had read-optimised columnar data that was overlaid with fresh write-optimised data and used timestamps to agree on the data that should be visible to the queries. It continuously consolidated data into the read-optimised store instead of having the silly daily job that you might have in the extremely slow cadence reporting job you mention.

You can write such a system, but in reality I've found it hard to justify building a system for continuous updates when a 15min delay isn't the end of the world, but it's doable if you want it.

> I'm not so sure about "continuously maintaining both means duplication and ensuring you get the worst case from both worlds". Maybe you're right, I'm just not so sure. I agree that it's duplicating storage requirements, but is that such a big deal? And I think if fast writes and lookups and fast batch reads are both possible at the cost of storage duplication, that would actually be the best case from both worlds?

I mean that if you want both views in a consistent world, then writes will bring things to a crawl as both, row and column ordered data needs to be updated before the writing lock is released.