Show HN: BlitzGraph – Supabase for graphs, built for LLM agents
blitzgraph.comHello HN After becoming allergic to SQL, I opened 120+ issues in Dgraph, Typedb and surrealdb looking for the perfect graphDB. None of them was built for agents nor were they the perfect fit for what we wanted to achieve: fully ditching the SQL legacy to properly model reality. So we decided to build BlitzGraph
In BlitzGraph, records (units) can belong to multiple types (kinds) and evolve through time. Also polymorphic relations are first class and multiple kinds can play the same role. This design helps to escape the old table paradigm and track entities throughout their lifecycle without awkward self-joins that connect an entity to itself under different IDs in other tables
An example:
{ "$id": "amazn", "$kinds": ["Company", "Prospect"], deal: ... } // Day 1
{ "$id": "amazn", "$kinds": ["Company", "Customer"], contract: .. } // Day 7
{ "$id": "amazn", "$kinds": ["Company", "Churned"], churnCause: "..." }, ... // Day 86
- GraphQL-like nested queries and mutations https://blitzgraph.com/docs - Polymorphic records and relations
- Bidirectional O(1) relations - Referential integrity with native cardinality validations
- JSON query/mutation language designed so AI agents can build them programatically - Batched queries/mutations without N+1 issues
- Built-in frontend engine for quick dashboards and MVPs - Native full text search, file storage, computed fields, ephemeral subspaces, unit history...
- vs typedb: amazing db, but not ideal for app development. On the other hand we loved and brought their inference ideas and how mutations execute smartly instead of line per line - vs surrealdb: Several core differences, a key one is that we run validations and trasnformations in topological order, and our edges are first class citizens - vs dgraph: Their cool features like post commit hooks were attached to the graphQL layer, in BG it is fundational - neo4j: If you've tried it, you know - vs supabase/pg: BG is slower for flat queries but faster in nested ones. But with BG mainly you get rid of the tables paradigm and jump into the graph world while being able to build apps
Not ready:
- While blitzgraph is already an excellent memory backend for AI agents, we still need to finish the semantic search engine - Query planner is not optimized - Cloud frontends have no native auth engine yet
Beta is live, please break things!
- Public playground: https://blitzgraph.com/#playground
- MCP: https://blitzgraph.com/mcp "BlitzGraph beta · data may be wiped without notice · expect resets" This is not beta. This is alpha. - - - After becoming allergic to SQL, I opened 120+ issues in Dgraph, Typedb and surrealdb looking for the perfect graphDB. What were those 120+ issues supposed to do? That sounds suspiciously like something OpenClaw would think is a good idea. And surely only an agent would think it a good idea to brag about here. Just build a decent rdf database, with SPARQL, basic inferencing and SHACL support rather then reinventing another thing have never tried them before. do you have to configure/assemble these things? do you then run them as separate processes? what makes you say that you're more suitable for agents compared to say neo4j and typedb? is it the temporal modeling? congratulations for the beta by the way! Not the blitz author. Neo4j was freaking slow when I tried to use it. > I opened 120+ issues in Dgraph, Typedb and surrealdb looking for the perfect graphDB Can you share some examples? What was wrong with those? SQL isn't an allergy. It's time test. Take medicine to fix your allergy. Supa, Burschi!