BlitzGraph – Supabase for graphs, built for LLM agents
Hello 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…
In plain words
BlitzGraph is a graph database designed specifically for LLM agents as an alternative to traditional SQL databases. It allows records to belong to multiple types simultaneously and evolve over time, with polymorphic relations as a core feature. This approach eliminates the need for awkward self-joins and enables proper tracking of entities throughout their lifecycle without forcing data into a rigid table structure. The system models relationships more naturally than legacy relational databases.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hello 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 What makes BlitzGraph different: - 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... Honest comparisons: - 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
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