Weaviate
Open source vector database with hybrid search, modular retrieval and managed cloud options for production RAG and semantic apps at any scale.
Overview
Weaviate stores embeddings with schema aware classes and provides robust search operators for semantic, hybrid and filtered queries. Developers build retrieval augmented generation backends with tight control over recall and latency, while the modular stack supports pluggable text and multimodal embeddings. The managed Weaviate Cloud offers shared and dedicated clusters with simplified pricing and add ons like hosted embeddings and a query agent that translates natural language to database operations.
Enterprises deploy with HA, backups and role controls, while open source users self host for full flexibility. Clear SDKs in Python, TypeScript and Go and a GraphQL like API make integration straightforward across services and frameworks.
Key features
- Schema aware vector store with filters hybrid BM25 and metadata
- Managed cloud with shared clusters and HA plus backups
- Hosted embeddings add on for simple end to end setup
- Query Agent to convert natural language into operations
- SDKs for Python TypeScript Go and a clean HTTP API
- Sharding replication and snapshots for resilience at scale
- Multimodal vectors for text image and custom embeddings
- Observability and usage metering in cloud console
Best for
- Power RAG backends that mix semantic and keyword filters
- Search product catalogs with facets and relevance controls
- Index documents and images for unified multimodal retrieval
- Prototype quickly in OSS then migrate to managed cloud
- Serve low latency queries for chat memory or agents
- Automate backups and snapshots for compliance
- Use cloud hosted embeddings to skip model hosting
- Apply fine grained filters for policy aware responses
Capabilities
Schema and Vectors
Define classes properties and metadata then index embeddings to enable filtered semantic retrieval.
Hybrid and Filters
Combine vector similarity with BM25 and metadata filters for precise low latency results.
Managed Cloud
Use shared HA clusters with backups metrics and add ons like hosted embeddings and query agent.
SDKs and API
Adopt Python TypeScript and Go SDKs or call the HTTP API directly for any stack.
Frequently Asked Questions
How does pricing start?
Open source is free, Weaviate Cloud lists entry shared clusters with HA around $45 per month plus usage based add ons.
Can I bring my own embeddings?
Yes, you can store any vectors and also use hosted embeddings as an add on.
Is it suitable for production RAG?
Yes, teams deploy Weaviate for low latency hybrid retrieval with filters and backups.
Does it support multimodal data?
Text and image vectors are supported with flexible schema for custom types.
Can I self host?
Yes, run OSS on your own infra and migrate to cloud later.
Is there a query builder?
A Query Agent add on translates natural language to database operations to speed prototyping.
What SDKs are available?
Python, TypeScript and Go SDKs are maintained along with a GraphQL like API.
How are backups handled?
Cloud includes snapshot and backup features with console controls and APIs.
