Show HN: BlitzGraph – Supabase for graphs, built for LLM agents (blitzgraph.com)
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
14 comments
[ 3.0 ms ] story [ 43.6 ms ] threadcongratulations for the beta by the way!
Say you want to build a context layer for your company with BlitzGraph. Agents would use ephemeral subspaces to gather as much info as possible prior to re-categorize it, store files natively, keep episodic memories, track everything that happens to each memory or record with the native $history. Also the query language is in JSON, so it's easy to build programatically, it'sis strongly typed, and errors are written to guide agents to fix them. Agents can also batch-query docs, which are dense and straight to the point for token optimization (and the discovery tree for related docs is also optimized for them)
The long term objective is to become the "brain" or logic/storage layer of AI agents
Can you share some examples? What was wrong with those?
We did borrow the inference ideas tho, the inference/recursive relations are on the oven!
This is not beta. This is alpha.
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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.
On the issues: those were filed by hand over a couple of years trying to ship products on these DBs. Probably came across as bragging but the point was that I spent a big chunk of my life digging into graph and modern databases, and the gaps pushed me to give up and build one that gathers all their best ideas