# TileDB Vector Search

> TileDB Vector Search is a scalable open-source vector database that stores and performs approximate nearest neighbor searches on high-dimensional dense and sparse vectors using TileDB's multi-dimensional array storage for petabyte-scale data. Key features include Vamana graph and IVF-PQ indexing, metadata filtering, multi-tenancy, serverless scalability on object stores like S3, and APIs in Python/C++ with gRPC support. Suited for RAG pipelines, recommendation systems, and anomaly detection; excels in sparse vector efficiency and cost savings compared to Milvus or Pinecone, while scaling better than Faiss for large production deployments.

- **URL:** https://github.com/TileDB-Inc/TileDB-Vector-Search
- **Category:** Core Vector Databases
- **Tags:** Open Source, Scalable ANN, 2026 Production, Production Use, 2026 Ready
- **Updated:** 2026-04-28 11:38
- **Canonical page:** https://vectordb.ever.works/items/tiledb-vector-search

## Details

## Overview

TileDB Vector Search is a vector search solution leveraging the TileDB array storage format for high-performance similarity search.

## Key Components

- **apis/python**: Python bindings and APIs for integration.
- **demos**: Example applications and use cases.
- **documentation**: Comprehensive guides and references.
- **src**: Core C++ implementation.
- **.github/workflows**: CI/CD pipelines.

## License

MIT License.

## Pricing

Free and open-source.

---

_This Markdown mirror is generated by Ever Works for AI agents. The canonical HTML page is at https://vectordb.ever.works/items/tiledb-vector-search._