WeftKitGraph
Graph Database
Native property graph database with Cypher-like query language, BFS/DFS traversals, shortest path algorithms, and CSR/CSC storage format.
BFS 100-vertex traversal
Key Features
What makes WeftKitGraph stand out.
Native Graph Storage
CSR/CSC (Compressed Sparse Row/Column) format for efficient traversal operations. Adjacency lists with property payloads.
Cypher-like Query Language
Familiar graph query syntax for MATCH, WHERE, RETURN, CREATE, MERGE, DELETE operations. Pattern matching on subgraphs.
Graph Algorithms
BFS, DFS, shortest path (Dijkstra, A*), PageRank, connected components, community detection. Parallel execution for large graphs.
Property Graph Model
Nodes and edges with arbitrary key-value properties. Multi-label nodes. Named edge types. Bidirectional traversal.
In-memory Acceleration
Hot graph regions cached in memory for sub-microsecond traversal. LRU eviction with access frequency tracking.
Sub-graph Export
Export sub-graphs as JSON, GraphML, or Cypher statements. Integration with graph visualization tools.
Performance Targets
Real numbers from Criterion benchmarks on reference hardware.
Wire Protocol
WeftKitGraph supports the Bolt Protocol (Neo4j compatible) protocol. Your existing tools just work.
Get Started in Seconds
Add WeftKitGraph to your Rust project and start querying.
use weftkitgraph::prelude::*;
// Open or create a database
let db = Database::open("my_app.db")?;
// Use the module API
let result = db.query("SELECT * FROM users WHERE active = true")?;
for row in result.rows() {
println!("{:?}", row);
}Where to Use It
Social networks and relationship graphs
Fraud detection and graph analytics
Knowledge graphs and ontologies