SatoriDB – Query 1B vectors on a laptop (SQLite for embeddings, Rust)
High performance embedded vector database. Contribute to nubskr/satoriDB development by creating an account on GitHub.
SatoriDB – Query 1B vectors on a laptop (SQLite for embeddings, Rust) launched on December 30, 2025 with 5 votes, #2,550 of 11,628 launches that month and more than 75% of that year's launches.
What it does
SatoriDB is an embedded vector database built for bigger than memory workloads for ANN search and handles billion scale datasets with 95%+ recall and predictable latencies. SatoriDB is a two-tier search system: a small "hot" index in RAM routes queries to "cold" vector data on disk. This lets us handle billion-scale datasets without holding everything in memory. Quantized HNSW index over bucket centroids. Centroids are scalar-quantized (f32 → u8) so the whole routing index fits in RAM even at 500k+ buckets. When a query comes in, HNSW finds the top-K most relevant buckets in O(log N). We only search those, not the entire dataset. CPU-pinned Glommio workers scan selected buckets in parallel.…from github.com
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