Hey folks — I’m currently working on some AI-driven applications, and have concerns with how to integrate supabase with other data systems whenever:
- mixing Postgres + vector DB + external data sources/APIs, such as delta lake
- keeping data consistent across them
- debugging becomes pretty painful once things go wrong
Curious if others here are dealing with similar problems? Would love to compare notes or learn how you’re structuring things — especially if you’ve tried to unify the data access layer in a way to make it build easier and faster.
The user is seeking advice on integrating Supabase with multiple data systems, including Postgres, vector databases, and external sources like Delta Lake. They are concerned about data consistency and debugging challenges and are looking for ways to unify the data access layer for easier and faster development.
scaylor handles the multi-source unification problem pretty well since it auto-maps data from different systems into one queryable layer, though it's more geared toward ERP and business data than vector DBs specifically. for your postgres plus vector setup you might also look at Prisma if you want a clean ORM abstraction across data sources, but you'll still be writing the consistency logic yourself. another option is just building a thin service layer with something like Hasura to federate your queries, though debugging distributed state is still gonna be painful no matter what you use tbh.
the tradeoff is basicaly control versus convienence. Scaylor leans toward convenience if your data sources are more traditional.