Overview
Graph database superpowers for your existing Postgres data.
pgGraph lets you run complex graph queries, like finding shortest paths, mapping relationships, and discovering networks, directly on your existing PostgreSQL tables using standard SQL. You don’t need to migrate your data to a separate graph database, and your app keeps writing data the exact same way it always has. Postgres remains your single source of truth.
Finding Shortest Path
Mapping Relationships
Discovering Networks
Quick Links
pgGraph is currently alpha software for experimentation, demos, benchmarks, and early feedback. The core graph features are usable, but memory hardening for very large graphs and expensive algorithms is still in progress. Run it in Docker or a dedicated development database for now, not on a production or shared PostgreSQL cluster.
Evokoa
pgGraph is built by Evokoa . We are building the missing infrastructure for widespread AI adoption. We are committed to keeping pgGraph 100% free and open-source, forever.
Star our repo to help us reach more developers, and follow our journey below:
How it Works
pgGraph builds a compact, derived graph index over selected relational tables for repeated bounded traversal workloads. Because Postgres stays the system of record, all standard tables, constraints, WAL, MVCC, backups, ACLs, and RLS still apply to application writes.
Core Architecture
PostgreSQL tables stay authoritative. pgGraph is derived acceleration state. Users ask SQL questions; hot loops walk integer arrays.
pgrx Boundary
SQL arguments enter through pgrx, and final rows return through pgrx to PostgreSQL. The engine operates on compact graph data without recursive SQL.
CSR: The Hot Path Shape
pgGraph stores edges as compressed sparse row (CSR) arrays. Expansion involves simply slicing flat parallel arrays, avoiding pointers and object chasing.
Hover over a node to see its array slice
Immutable Base, Mutable Overlay
Fast immutable base structure shared by the OS page cache, with bounded backend-local mutable overlays to immediately absorb real-time inserts and deletes.
Current benchmarks
Query Performance
Dataset: PANAMA (2,016,523 nodes, 5,802,586 edges)
Cold Run (ms)
Hot Run (ms)
* Cold Run: Docker container restart before each cold query; excludes graph.build(); OS cache may remain warm depending on host
* Hot Run: one unrecorded warm-up pass, then repeated measured SQL in one persistent psycopg PostgreSQL backend
Query Performance
Dataset: LDBC (3,181,724 nodes, 34,512,076 edges)
Cold Run (ms)
Hot Run (ms)
* Cold Run: Docker container restart before each cold query; excludes graph.build(); OS cache may remain warm depending on host
* Hot Run: one unrecorded warm-up pass, then repeated measured SQL in one persistent psycopg PostgreSQL backend
Machine Info: macOS-26.4-arm64-arm-64bit | 14 CPUs | Captured: 5/12/2026
Current Scope
Currently Supported →
PostgreSQL 13-18
Compatible with PostgreSQL 13 through 18. Primarily tested on PostgreSQL 17.
Schema Registration
Register tables and edges manually, or use auto-discovery for fast setup.
SQL-backed Search
Search over registered columns using contains, exact, prefix, and token modes.
Graph Traversal
Bounded BFS and DFS with depth, frontier, filtering, pagination, and circuit breakers.
Shortest Path & Components
Standard and weighted shortest paths, plus connected component summaries.
Filtering & Aggregation
Typed filter pushdown and JSON traversal specs for server-side aggregates.
Sync & Maintenance
Trigger-buffered capture, explicit apply, background jobs, and full rebuild vacuum.
Fast Persistence
Atomic .pggraph artifacts with mmap-backed arrays for fast backend startup.
Roadmap & Future Work →
Semantic-Guided Search
Vector-distance ranking with pgVector to prioritize relevant paths during traversal.
WAL Streaming Sync
Logical replication based sync to avoid trigger-buffer volume.
COPY Build Scanner
A server-side COPY scanner to optimize large-scale graph builds.
Online Mutable CSR
Append or delta structures to reduce rebuild pressure without weakening correctness.
Full A* Path Search
Specialized semantic-guided search mode using admissible heuristics.
Global Analytics
Companion analytics paths for PageRank, Louvain, and betweenness.
Distributed Execution
Scaling graph execution across distributed PostgreSQL instances.
Documentation
License
Apache-2.0. See LICENSE .
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