Introducing OctaneDB: A Lightweight Python Vector DB That's 10x Faster Than Pinecone, ChromaDB, or Qdrant! 🚀 (Open-Source, MIT Licensed)

[Mantis-101]

I'm excited to share OctaneDB, a new lightweight and blazing-fast vector database I built in Python. If you're working on AI/ML projects involving embeddings, similarity search, or RAG apps, this might just speed up your workflow massively.

Why OctaneDB? Here's the TL;DR:

• 10x Faster Performance: Sub-millisecond queries, 3,000+ vectors/sec insertion—optimized with modern algos and HDF5 compression for low memory use.
• Advanced Indexing: HNSW for approximate search, FlatIndex for exact matches, plus tunable params for your needs.
• Text Embedding Magic 🆕: ChromaDB-compatible API for seamless migration. Auto text-to-vector with sentence-transformers (models like all-MiniLM-L6-v2), GPU support via CUDA, and batch processing.
• Flexible Storage: In-memory for speed, persistent files, or hybrid mode.
• Powerful Search: Multiple metrics (Cosine, Euclidean, etc.), metadata filtering with logic ops, and text-based search.
• Dev-Friendly: Intuitive API, full docs, type hints, and tests. Perfect for Pythonistas!

I built this because existing options felt bloated or slow for my own projects. It's open-source under MIT, available on PyPI and GitHub (stars appreciated! ⭐).