pgGraph
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
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.
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How it Works
pgGraph builds a compact graph index over selected relational tables to make repeated traversal queries faster. Because Postgres remains the system of record, its tables, constraints, WAL, MVCC, backups, ACLs, and RLS still apply to application writes.
pgGraph can persist the graph index for faster startup. It updates persisted indexes atomically, so a backend loads either the previous complete index or the new one, never a partial update. If an index is missing or invalid, pgGraph can rebuild it from the PostgreSQL tables.
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.
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)
Query Performance
Dataset: LDBC (3,181,724 nodes, 34,512,076 edges)
Current Scope
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.
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 .