LanceDB
FreemiumEmbedded vector database built on the Lance columnar format for search over object storage.
Tool Info
Overview
LanceDB is an in-process vector database built on the open Lance columnar format.
It runs embedded over local or object storage and supports vector, full-text, and hybrid search.
LanceDB Cloud and Enterprise add managed and distributed deployments.
Features
- In-process embedded engine
- Lance columnar format
- IVF-PQ and HNSW indexes
- Full-text and hybrid search
Pricing
Pros
- No separate server to run
- Runs over object storage
- Multimodal and versioned data
Best For
When NOT to Use
- Smaller ecosystem than peers
- Newer managed and enterprise tiers
Typical Users
Related Tools
Alternatives
Related Architecture Guides
Tags
Related Guides
- Vector Search
Understand how vector databases find similar items using high-dimensional embedding comparisons.
- Embeddings
Discover how AI converts text, images, and data into numerical vectors that capture meaning.
- Vector Quantization
Compress embedding vectors with product, scalar, and binary quantization to cut memory and speed ANN search with controlled recall tradeoffs.
- ANN Indexes
Approximate nearest neighbor indexes - HNSW, IVF, IVF-PQ, DiskANN, ScaNN, and flat - that make vector search fast at scale.
- RAG
A comprehensive guide to RAG - the dominant pattern for building AI applications that answer questions using your own data.
- Hybrid Search
Combine keyword and semantic search for more accurate and comprehensive information retrieval.
- Semantic Search
Learn how AI understands the meaning behind queries to find relevant results beyond keyword matching.
- Vector Databases
Purpose-built databases for storing, indexing, and querying embedding vectors at scale.
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