TileDB-Inc/TileDB-Vector-Search
Cloud-native vector similarity search and storage with efficient, serverless scale-out
This helps developers integrate highly efficient, scalable vector search capabilities into their applications. It takes high-dimensional numerical data (vectors) representing things like text embeddings or image features, and allows you to quickly find the most similar items. This is ideal for AI/ML engineers or data scientists building recommendation systems, semantic search, or anomaly detection features.
Available on PyPI.
Use this if you need to perform fast similarity searches on large datasets of high-dimensional vectors and require cloud-native scalability and storage.
Not ideal if you are looking for an out-of-the-box application for vector search rather than a library to integrate into your own systems.
Stars
66
Forks
11
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 16, 2025
Commits (30d)
0
Dependencies
5
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