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Weaviate Freemium
Open-source vector database with hybrid search and built-in embedding modules
Weaviate is an open-source vector database built for AI applications. It stores embeddings alongside raw objects and supports hybrid search that blends keyword (BM25) and vector similarity, which makes it a common backend for RAG and recommendation systems. Self-hosting is free; Weaviate Cloud starts with a sandbox.
What is Weaviate?
Weaviate is a database written in Go that treats vectors as first-class citizens. You define a schema, hand it text, and it can generate embeddings for you through modules — no separate embedding service required for the basics. It was founded in Amsterdam in 2019 and is now used by teams that need semantic search without bolting a vector index onto Postgres.
What features does Weaviate offer?
- Hybrid search: combine BM25 keyword matching with vector search and weigh them, so exact terms and semantics both count.
- Built-in modules: text2vec modules for OpenAI, Cohere, Hugging Face and others.
- Reranking: cross-encoder rerankers to reorder the top results before you send them to a model.
- Multi-tenancy: isolate customer data per tenant in one cluster, useful for SaaS.
- GraphQL and REST: query with GraphQL; the client libraries cover Python, TypeScript, Java and Go.
Weaviate highlights
- BSD-3 license; run it yourself on Docker or Kubernetes for free.
- Cloud sandbox is free with limited dimensions; paid tiers bill on usage.
- Horizontal scaling and replication are built in, not bolted on.
What can you build with Weaviate?
- Semantic search over product catalogs where exact SKUs still matter.
- A RAG chatbot over internal wikis with per-team tenants.
- Recommendation engines using embedding similarity.
- Duplicate detection across large document sets.
- Multimodal search over images paired with captions.
It suits backend engineers who want control and can run infrastructure. If you want a wholly managed, zero-ops experience, Pinecone or a managed Postgres with pgvector may be simpler. The learning curve around schema and modules is real, and self-hosting costs you ops time.
Quick Summary
- Weaviate is an open-source vector database under the BSD-3 license.
- It supports hybrid search mixing BM25 and vector similarity.
- Embedding and reranking modules run inside the database.
- Self-hosting is free; Weaviate Cloud offers a free sandbox and paid tiers.
- Best for engineers who want infrastructure control.
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