Results for vector_record

Fast embedded vector database with incremental HNSW indexing.

Fast embedded vector database with incremental HNSW indexing.

Embedded vector database for Rust. Lock-free, allocation-free hot path; cross-platform similarity search.

A high-performance hybrid embedded database in pure Rust with KV, records, graph, and vector support

Educational in-memory vector DB: WAL + bincode snapshots (TOON header), IVF bucket search, Axum REST API, TOON query responses

A high-performance vector database core for reading and writing historical records such as logs and chat records

Schema-free, natural language storage engine

Pure-Rust AVIF (AV1 Image File Format) decoder — HEIF meta-box walk + primary-item / av1C extraction, handed to oxideav-av1 for end-to-end pixel decode; grid + alpha + irot/imir/clap composition

FSVI vector index, SIMD dot product, and top-k search for frankensearch

Backend-agnostic storage, tiered memory, and document management for the Brainwires Agent Framework

AXON v1.5.1 — first crates.io publication of the AXON language full-stack runtime. Lexer/parser/type-checker/IR generator (re-exported from axon-frontend) plus the native Rust runtime: typed channels (TypedEventBus with QoS×5, π-calculus mobility, capability extrusion via shield D8 — Fase 13.f.2), Free Monad CPS handlers (Fase 2), lease kernel + reconcile loop (Fase 3+5), Epistemic Security Kernel (ESK Fase 6), Trust Types + ReplayLog (Fase 11.a+11.c), Stateful PEM over WebSocket (Fase 11.d), Ontological Tool Synthesis (Fase 11.e), Mobile Typed Channels (Fase 13). Crate publishes as `axon-lang` to mirror the Python PyPI package; library import remains `use axon::*` so existing call sites keep working unchanged.

Fast, lightweight, in-process vector database with HNSW indexing, E8/H4 lattice quantization (up to 24.8x compression), metadata filtering, and PyO3 bindings