Crate anda_db_hnsw 

Anda-DB HNSW Vector Search Library

A high-performance implementation of Hierarchical Navigable Small World (HNSW) algorithm for approximate nearest neighbor search in high-dimensional spaces.

HNSW is a graph-based indexing algorithm that creates a multi-layered structure to enable fast and accurate nearest neighbor search in high-dimensional spaces.

Features

• Fast approximate nearest neighbor search;
• Multiple distance metrics (Euclidean, Cosine, Inner Product, Manhattan);
• Configurable index parameters;
• Thread-safe implementation with concurrent read/write operations;
• Serialization and deserialization support;
• Support for bf16 (brain floating point) vector storage for memory efficiency.

Re-exports

pub use half;

Structs

HnswConfig

HNSW configuration parameters.

HnswIndex

HNSW index for approximate nearest neighbor search.

HnswMetadata

Index metadata.

HnswNode

HNSW graph node.

HnswStats

Index statistics.

LayerGen

Random layer generator for HNSW

Enums

DistanceMetric

Distance metric types.

HnswError

Errors that can occur when working with HNSW index.

SelectNeighborsStrategy

Neighbor selection strategies.

Functions

serialize_node

Serializes a node to binary in CBOR format.

Type Aliases

BoxError