t
turbovec
A vector index built on TurboQuant, written in Rust with Python bindings
open-sourcememory-knowledge
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Overview
turbovec is a vector index built on Google Research's TurboQuant algorithm, offering online ingest without a training phase and fast SIMD search. It provides incremental saves, filtered search capabilities, and is designed for local, privacy-focused RAG stacks.
Deep Analysis
Key Differentiator
Fits a 10M document corpus in 4GB RAM with faster search than FAISS using TurboQuant's data-oblivious quantization.
⚡ Capabilities
- • vector indexing
- • online ingest without training
- • fast SIMD search
- • incremental saves
- • filtered search
- • hybrid retrieval
🔗 Integrations
Python bindingsany open-source embedding model
✓ Best For
- ✓ RAG applications where privacy matters
- ✓ memory-constrained environments
- ✓ local/air-gapped AI agent stacks
✗ Not Ideal For
- ✗ managed vector database services
- ✗ end-user AI applications
⚠ Known Limitations
- ⚠ Pure local solution (no managed service)
- ⚠ Requires casting to float32 arrays
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