We're building an open-source Text2SQL tool that transforms natural language into SQL using graph-powered schema understanding. Allowing you to ask your database questions in plain English, QueryWeaver handles the "weaving".

https://github.com/FalkorDB/QueryWeaver/

can you share a link?

The fact that GQL is now supported by some of the relational Database, doesn't mean they'll become an alternative to native Graph Databases.

Yeah I guess it’s like saying that relational DBs supporting native JSON type meant the end of NoSQL DBs.

>relational DBs supporting native JSON type meant the end of NoSQL DBs

This holds true for 95% of cases of well-made software.

It pretty much did except for very specific use cases

You should check FalkorDB https://github.com/falkordb/falkordb

Not embedded last I checked. Unless that changed.

Did you try to run redis-benchmark? (Compared to Redis)

We built QueryWeaver exactly to solve those pain points—SQL generation that actually understands your business context and keeps the conversation alive across follow-ups. The graph layer is fully extensible, so you can define things like what an “active user” means for your org. Would love to hear your feedback if you give it a try!

You can find the release notes here: https://github.com/FalkorDB/FalkorDB/releases/tag/v4.10.0

Much more than that, FalkorDB added many features on top of RedisGraph.

Your graph DB frustrations mirror what many experienced with Neo4j. If you refresh your project, consider including FalkorDB (formerly RedisGraph) - it uses sparse adjacency matrices and GraphBLAS for much better performance while supporting Cypher.

Would be interesting to see updated benchmarks comparing these newer options against PostgreSQL extensions.

The QirK paper is super interesting https://arxiv.org/pdf/2408.07494.

We took that one step further with the GraphRAG-SDK - https://github.com/FalkorDB/GraphRAG-SDK