I've been working on adding graph database capabilities to SQLite with support for the Cypher query language. As of this week, both CREATE and MATCH operations work with full relationship support.

Here's what it looks like:

    import sqlite3
    conn = sqlite3.connect(":memory:")
    conn.load_extension("./libgraph.so")
    
    conn.execute("CREATE VIRTUAL TABLE graph USING graph()")
    
    # Create a social network
    conn.execute("""SELECT cypher_execute('
        CREATE (alice:Person {name: "Alice", age: 30}),
               (bob:Person {name: "Bob", age: 25}),
               (alice)-[:KNOWS {since: 2020}]->(bob)
    ')""")
    
    # Query the graph with relationship patterns
    conn.execute("""SELECT cypher_execute('
        MATCH (a:Person)-[r:KNOWS]->(b:Person) 
        WHERE a.age > 25 
        RETURN a, r, b
    ')""")

The interesting part was building the complete execution pipeline - lexer, parser, logical planner, physical planner, and an iterator-based executor using the Volcano model. All in C99 with no dependencies beyond SQLite.

What works now: - Full CREATE: nodes, relationships, properties, chained patterns (70/70 openCypher TCK tests) - MATCH with relationship patterns: (a)-[r:TYPE]->(b) with label and type filtering - WHERE clause: property comparisons on nodes (=, >, <, >=, <=, <>) - RETURN: basic projection with JSON serialization - Virtual table integration for mixing SQL and Cypher

Performance: - 340K nodes/sec inserts (consistent to 1M nodes) - 390K edges/sec for relationships - 180K nodes/sec scans with WHERE filtering

Current limitations (alpha): - Only forward relationships (no `<-[r]-` or bidirectional `-[r]-`) - No relationship property filtering in WHERE (e.g., `WHERE r.weight > 5`) - No variable-length paths yet (e.g., `[r*1..3]`) - No aggregations, ORDER BY, property projection in RETURN - Must use double quotes for strings: {name: "Alice"} not {name: 'Alice'}

This is alpha - API may change. But core graph query patterns work! The execution pipeline handles CREATE/MATCH/WHERE/RETURN end-to-end.

Next up: bidirectional relationships, property projection, aggregations. Roadmap targets full Cypher support by Q1 2026.

Built as part of Agentflare AI, but it's standalone and MIT licensed. Would love feedback on what to prioritize.

GitHub: https://github.com/agentflare-ai/sqlite-graph

Happy to answer questions about the implementation!