The AgensGraph Development Team is pleased to announce the release of AgensGraph v2.18.6.1, the latest version in the 2.18 series. AgensGraph is an open-source graph database, built on PostgreSQL 18.6, that runs SQL and graph queries over the same data, in the same transaction and even in the same statement.

AgensGraph 2.18 is a major step toward the ISO GQL standard (ISO/IEC 39075), the international standard query language for property graphs. We are committed to bringing AgensGraph in line with GQL: 2.18 adds the first set of GQL clauses alongside openCypher, and more will follow in upcoming releases.

Performance was the other focus of this release. Variable-length traversals now use the edge label's index at each hop, whereas 2.17 scanned the entire label at every hop. On the public soc-Pokec graph (30 million edges), a two-hop traversal that did not finish within 20 seconds in our tests on 2.17 now completes in milliseconds.

Highlights

  • GQL clauses: LET, FOR, FILTER, NEXT, FINISH and INSERT, plus standalone ORDER BY, OFFSET and LIMIT clauses.
  • Graph subqueries: CALL { }, OPTIONAL CALL, EXISTS { }, COUNT { }, COLLECT { } and VALUE { }, plus CALL ... YIELD to invoke PostgreSQL functions from Cypher.
  • Based on PostgreSQL 18.6: asynchronous I/O, uuidv7(), virtual generated columns, OAuth authentication, B-tree skip scan and all PostgreSQL fixes through 18.6.
  • Faster graph queries: variable-length traversals, pattern matching, label scans, EXISTS subqueries, path functions, sorting, grouping and counting of vertices and edges, ordering by vector distance, and the SET and DELETE clauses.
  • Typed property columns: frequently queried properties can be stored as native typed columns and indexed like any other PostgreSQL column for faster filtering and sorting.
  • Security: Cypher writes now enforce row-level security policies, and fixed-length patterns also enforce row-level security and privileges on labels they match without naming them.

AI and Python

  • agensgraph-python 2.1: a major new version of the Python driver, rebuilt on psycopg 3. It supports both synchronous and asynchronous code, runs Cypher and SQL in the same transaction, and returns vertices, edges and paths as native Python objects. Query results load straight into pandas, Polars or Arrow for analytics, and connection pooling, bulk loading and OpenTelemetry tracing are available.
  • agensgraph-ai: integrations for building GraphRAG and knowledge-graph applications with LangChain (including a LangGraph checkpointer and store), LlamaIndex, LightRAG and cognee, plus Model Context Protocol (MCP) servers that let AI assistants work with your graph.
  • Graph and vectors together: with the pgvector extension (installed separately), graph data and vector embeddings live in the same database, so a single query can combine graph traversal with vector similarity search.

Upgrading

A 2.17 data directory cannot be used directly with 2.18. Upgrade with pg_upgrade, or dump with the 2.18 version of pg_dump and restore. Before you start, review what changed from 2.17. Installations already on 2.18.6.0 only need to replace the binaries and restart.

Links

About AgensGraph

AgensGraph is a multi-model graph database that extends PostgreSQL with openCypher and ISO GQL clauses, released under the Apache License 2.0. It has been developed since 2016 by SKAI Worldwide (formerly Bitnine).