cd /news/large-language-models/show-hn-blitzgraph-supabase-for-grap… · home topics large-language-models article
[ARTICLE · art-29720] src=blitzgraph.com ↗ pub= topic=large-language-models verified=true sentiment=↑ positive

Show HN: BlitzGraph – Supabase for graphs, built for LLM agents

BlitzGraph, a new graph database built for LLM agents, launches in beta on Hacker News. The database supports polymorphic records and relations, time-evolving entities, and a JSON query language designed for AI agents, aiming to replace traditional SQL-based systems. BlitzGraph is positioned as a memory backend for AI agents, with features like bidirectional O(1) relations and native full-text search.

read2 min views2 publishedJun 16, 2026

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 docs>
   - Polymorphic records and relations
   - Bidirectional O(1) relations
   - Referential integrity with native cardinality validations
   - JSON querymutation 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 with

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!

Comments URL: https://news.ycombinator.com/item?id=48557002

Points: 1

── more in #large-language-models 4 stories · sorted by recency
── more on @blitzgraph 3 stories trending now
sponsored brought to you by zahid.host 4,200+ EU-deployed projects
reading about agents? ship yours in a single git push.

Run your AI side-project on zahid.host

EU-based hosting, git-push deploys, automatic HTTPS, no cold starts. Free tier with a custom domain — perfect for shipping the agent you just read about.

$git push zahid main
Live at https://your-agent.zahid.host
Get free account → Pricing
from €0/mo · no card required
LIVE [news/show-hn-blitzgraph-s…] indexed:0 read:2min 2026-06-16 ·