GraphBLAS
A standard for graph algorithms based on sparse matrices, used to efficiently express and compute operations such as graph traversal and matrix multiplication. It often serves as the underlying storage and computation engine for graph databases.
Core Facts
Timeline (last 90 days)
FalkorDB has a built-in GraphBLAS matrix multiplication engine, supports the native OpenCypher query language, and executes multi-hop graph algorithms with sub-millisecond latency.
FalkorDB uses GraphBLAS matrix operations to represent the adjacency graph as sparse matrices, translating Cypher path queries into linear algebra matrix multiplications, so multi-hop reachability queries complete in single-digit milliseconds (<15ms).
FalkorDB's linear algebra engine (GraphBLAS) turns graph operations into sparse matrix computations on Redis
GraphBLAS is an open standard and C language interface specification for expressing linear algebra operations on graph structures, developed under the leadership of IEEE.
FalkorDB is built on GraphBLAS, representing nodes and relationships as sparse linear-algebra matrices.
GraphBLAS is a standard linear algebra interface for graph algorithms that represents graphs as sparse adjacency matrices and converts operations such as breadth-first search and multi-hop reachability into matrix multiplication or semiring operations.
As a Redis module, FalkorDB stores graphs using sparse matrices and GraphBLAS linear algebra; multi-hop traversal is essentially matrix multiplication, and 5-hop query latency stays stably within 15 milliseconds.
FalkorDB is a Redis-based graph database that supports the property graph model and the OpenCypher query language, includes a built-in graph algorithm module, and stores graph data as sparse matrices.
All Facts (8)
FalkorDB is a Redis-based graph database that supports the property graph model and the OpenCypher query language, includes a built-in graph algorithm module, and stores graph data as sparse matrices.
80%UnverifiedFalkorDB has a built-in GraphBLAS matrix multiplication engine, supports the native OpenCypher query language, and executes multi-hop graph algorithms with sub-millisecond latency.
50%UnverifiedFalkorDB uses GraphBLAS matrix operations to represent the adjacency graph as sparse matrices, translating Cypher path queries into linear algebra matrix multiplications, so multi-hop reachability queries complete in single-digit milliseconds (<15ms).
50%UnverifiedFalkorDB's linear algebra engine (GraphBLAS) turns graph operations into sparse matrix computations on Redis
50%UnverifiedFalkorDB is built on GraphBLAS, representing nodes and relationships as sparse linear-algebra matrices.
50%UnverifiedGraphBLAS is an open standard and C language interface specification for expressing linear algebra operations on graph structures, developed under the leadership of IEEE.
50%UnverifiedGraphBLAS is a standard linear algebra interface for graph algorithms that represents graphs as sparse adjacency matrices and converts operations such as breadth-first search and multi-hop reachability into matrix multiplication or semiring operations.
50%UnverifiedAs a Redis module, FalkorDB stores graphs using sparse matrices and GraphBLAS linear algebra; multi-hop traversal is essentially matrix multiplication, and 5-hop query latency stays stably within 15 milliseconds.
50%