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

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

48 points by itsezc 2 days ago | 3 comments

pgaddict 17 minutes ago |

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.

PunchyHamster 32 minutes ago |

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

stevefan1999 9 minutes ago | |

Projects that's using already existing that is using Postgres already should keep it in Postgres.

It is worth a try for startups if you won't mind. Try to vibe code around it and give the data model a new look. I have a prototype project that combines both tree-sitter AST and converted it to JSON, then since SurrealDB accepts JSON as native input I now get free graph lookup on the control flow and easily did ancestry analysis and finding what functions potentially calls to this segement. All of it is in SurrealDB nested graph queries and the performance is alright, but is abysmal in Postgres JSONB since JSONB does not linearize the JSON data structure.

ps: I'm building a K8S operator for deploying SurrealDB with TiKV operator integration too.

marcyb5st 2 minutes ago | |

Not in anyway related with the surreal folks.

I think it is not so clear cut. I mean, the multi-model nature it is pretty neat. Yes, you can use pgvector on PostgreSQL, but here you also have native graph support. If you want to have both you need to also add something like apache AGE, but arguably that is also a small ecosystem (at least IMHO as I never heard it until I actually started looking for Neo4J alternatives). Also, pgvector has a hard limit on embedding size, while surrealdb does not. For instances in which you have less than 1M elements and retrieval performance matters surreal already has an advantage.

In my personal opinion is a great overall product. Probably not the best at anything, but close enough without having to fiddle with PostgreSQL extensions or adding another piece of machinery to support graph workloads.

The only thing I don't like is that they didn't use either pure SQL nor Cipher for the query(ies) language(s). They roll their own blend, meaning that you will likely need more work to move in the ecosystem and you can't fully use the muscle memory of users that worked with other DBs before.