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by natdempk 88 days ago
Serious question: are there any actually good and useful graph databases that people would trust in production at reasonable scale and are available as a vendor or as open source? eg. not Meta's TAO
6 comments

That's a difficult question and I would like to avoid giving a direct answer (because I co-lead a nonprofit benchmarking graph databases) but even knowing what you need for a graph database can be a tricky decision. See my FOSDEM 2025 talk, where I tried to make sense of the field:

https://archive.fosdem.org/2025/schedule/event/fosdem-2025-5...

Serious answer: limiting to just Open Source: JanusGraph, DGraph, Apache AGE, HugeGraph, MemGraph and ArcadeDB all meet that criteria.
What is open source and what is a graph database are both hotly debated topics.

Author of ArcadeDB critiques many nominally open source licenses here:

https://www.linkedin.com/posts/garulli_why-arcadedb-will-nev...

What is a graph database is also relevant:

  - Does it need index free adjacency?
  - Does it need to implement compressed sparse rows?
  - Does it need to implement ACID?
  - Does translating Cypher to SQL count as a graph database?
What people perceive as "Facebook production graph" is not just TAO. There is an ecosystem around it and I wrote one piece of it.

Full history here: https://www.linkedin.com/pulse/brief-history-graphs-facebook...

I run the development of TypeDB, which doesnt use Cypher but works really well as a graph database. Certainly it, and other graph databases like neo4j, are used in production at scale. However, a lot of oss databases are open core on some level, it just depends on where they draw the line. We draw it at clustering/high availability for the time being, the rest is in the CE version.
plenty of those - I've had to work with dozens of different graph databases integrating them on https://gdotv.com, save for maybe 1-2 exceptions in the list of supported databases on our website, they're all production ready and either backed by a vendor or open-source (or sometimes both, e.g. Apache AGE for Azure PostgreSQL). There are some technologies that have been around for a long time but really flying under the radar, despite being used a lot in enterprise (e.g. JanusGraph).
Yeah: Postgres, etc.

When you actually need to run graph algorithms against your relational data, you export the subset of that data into something like Grafeo (embedded mode is a big plus here) and run your analysis.

That importing is expensive and prevents you from handling billion scale graphs.

It's possible to run cypher against duckdb (soon postgres as well via duckdb's postgres extension) without having to import anything. That's a game changer when everything is in the same process.