SpacetimeDB: a short technical review← Home<br>SpacetimeDB: a short technical review<br>2026-02-26<br>The database market is harsh, particularly for newcomers. It’s very hard to launch a new product and differentiate yourself from the incumbents. Even harder to gain any long term traction. Earlier this week, SpacetimeDB launched version 2.0 of their database with a peculiar approach that —as far as I can tell— hasn’t been done before: a slightly surreal (meme-y) video where they mock their competitors (drinking “competitor’s tears”) and a set of benchmarks that seem too good to be true (they are, indeed, not true), and that also mock other databases. Look at the cute magnifying glass next to the big losers of that benchmark. You gotta zoom in to see how much they suck! Good stuff.
I’ll be upfront and admit that I find this distasteful. But nonetheless, I think there are interesting ideas in this product, and I’d like to do a short technical review whilst being as fair as possible.<br>Benchmarks #<br>One common mistake newcomers to the database space make is believing that you can win by having “the best performance”. I’ve never seen this in practice. The (very few) companies that have built a sustainable database offering are winning by providing good, honest technical work that stands on its own. Of course, having benchmarks definitely helps with that. But then the benchmarks have to be good, honest technical work.<br>The ones that SpacetimeDB provided are none of those things. They have quite a few technical flaws in what they measure. You can see an alternate set of benchmarks here where SpacetimeDB stacks up very poorly against the competition.<br>Nonetheless, the big fundamental flaw in those benchmarks is that they’re not honest. And I get where they’re coming from, I do: they’re not honest because their database offering is something very different to the competition, and that makes it very enticing to write benchmarks like that. Their product is in a different segment of the database space, and they’re choosing to compare their product against databases that make different tradeoffs. It’s an appealing comparison, but it’s not a fair one.<br>I’ll give you an example of what this looks like, which I went through myself: a couple years ago I was working at PlanetScale and we shipped a MySQL extension for vector similarity search. We had some very specific goals for the implementation; it was very different from everything else out there because it was fully transactional, and the vector data was stored on disk, managed by MySQL’s buffer pools. This is in contrast to simpler approaches such as pgvector, that use HNSW and require the similarity graph to fit in memory. It was a very different product, with very different trade-offs. And it was immensely alluring to take an EC2 instance with 32GB of RAM and throw in 64GB of vector data into our database. Then do the same with a Postgres instance and pgvector. It’s the exact same machine, exact same dataset! It’s doing the same queries! But PlanetScale is doing tens of thousands per second and pgvector takes more than 3 seconds to finish a single query because the HNSW graph keeps being paged back and forth from disk.<br>It was indeed very alluring to show that in a benchmark. “We’re 10000 times faster than pgvector!”. But come on now. That’s not honest. Yes, it’s the same machine, the same dataset, and the same queries, but it’s not the same thing. We did not publish those benchmarks; instead we published a technical breakdown of the implementation, without unfair comparisons, which was very well received.<br>You don’t need “INSANE BENCHMARKS” to win at this. You just need solid technical work and solid technical writing explaining the trade-offs and limitations of your offering. You can see another example with Turbopuffer. Their benchmarks are not impressive, particularly when compared to their competitors. Their documentation has more lines discussing the things the database cannot do than the things it can do. But everyone knows that if your use case fits their offering, they have the best product for search in the market. Miles ahead of the competition. They don’t drink their competitors’ tears, they just quietly take their customers.<br>Anyway: back to SpacetimeDB and their benchmarks. They have a very different offering than their competitors! It’s an all-in-one database + application server, where you deploy a database instance and your application’s code runs inside the database itself. That’s a very interesting idea, I think. You could say it’s just like stored procedures in a relational database, but with better developer experience. Fair. But you can totally build a viable product out of that, though!<br>You gotta admit, however, that it has very little to do with the...