HelixDB vs Weaviate

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	HelixDB RAG	Weaviate RAG
Tagline	Unified graph-and-vector database built for AI agent memory and GraphRAG.	Open-source vector DB with hybrid search and modules.
Category	RAG	RAG
Pricing	Freemium· Open-source core; managed cloud pricing on request	Freemium· Free open-source; cloud from $25/mo
Model	—	Hosted vector DB (not an LLM)
Editorial score	—	8.4 / 10
Use cases	agent-memorygraphragvector-searchknowledge-graphenterprise-knowledge	self-hosted RAGhybrid search
Pros	Unifies graph, vector, and full-text search in one query layer Object-storage backend keeps costs and ops overhead lower than hot-memory stores Open source with SDKs in Rust, Go, TypeScript, and Python Temporal awareness for facts that change over time, useful for agent memory	Hybrid search built in Self-host or cloud Module ecosystem GraphQL + REST APIs
Cons	Younger project than Pinecone/Weaviate/Neo4j; smaller ecosystem and tooling Pricing for managed tier not transparent on the marketing site Object-storage tradeoffs may add latency vs in-memory vector DBs for hot paths	More ops than Pinecone if self-hosted Smaller community
Website	helix-db.com	weaviate.io

Pick HelixDB if

✅ Unifies graph, vector, and full-text search in one query layer
✅ Object-storage backend keeps costs and ops overhead lower than hot-memory stores
✅ Open source with SDKs in Rust, Go, TypeScript, and Python
✅ Temporal awareness for facts that change over time, useful for agent memory

Pick Weaviate if