Benchmarking SurrealDB 3.x vs. Postgres, Mongo, Neo4j and Redis (With Fsync)

I really wish they clearly documented the parameters used by each of the databases (or are we expected to dig those out of the .rs sources somehow?), and actual versions used (saying "Postgres" is ambiguous, it could be 14 or 18 - presumably it's 18, but who knows).

For example, I see they do this for Postgres:

`let max_wal_gb = (shared_buffers_gb).clamp(2, 16);`

2-16GB of WAL is not a lot, but I have no idea how large is the data set.

Note to others, since it wasn't obvious to me at first: their database is proprietary.

Regarding the benchmarks themselves, they would've been more interesting with reproducible steps and more hardware variety.

the surreal docs should not say "surreal is open source", it's source-available under the BSL

> MongoDB still leads on single-record writes, while SurrealDB is ~1.3× faster on reads

I greatly appreciate when a vendor is willing to run the test and publish unfavorable information, even if it's only in one benchmark category.

Benchmark dataset fits in memory. Not a good test.

I wish they would have compared with Google’s spanner db. I’ve found this database to be the fastest, multi region, globally distributed database by far.

So, just use PostgreSQL? 50% faster write at cost of 25% slower reads (which usually are prevailing workload) doesn't warrant moving into far smaller ecosystem

I'm pleased to see SurrealDB making progress. I look forward to the distributed comparisons. Can you also report TPC benchmarks? Also, do you have any write ups on your correctness- and regression testing approach?

Benchmarks are so misleading not only because of all the tunable parameters to make these hardly an Apples to Apples comparison, more fundamentally the way you would optimize for different engines involves different trade-offs, different data models with different indexes...