<p align="center">
  <img src="assets/pggraph-banner.png" alt="pgGraph Banner" />
</p>

<h1 align="center">pgGraph    <a href="https://docs.evokoa.com/pggraph/user_guide">
    <img src="https://img.shields.io/badge/docs-pgGraph-0ea5e9?style=flat-square" alt="pgGraph documentation">
  </a></h1>

<p align="center">
  <strong>Graph database superpowers for your existing Postgres data.</strong>
</p>

<p align="center">
  <a href="https://github.com/evokoa/pggraph">
    <img src="https://img.shields.io/github/stars/evokoa/pggraph?style=flat-square&logo=github&label=stars" alt="GitHub stars">
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  <a href="https://github.com/evokoa/pggraph/releases">
    <img src="https://img.shields.io/badge/version-1.1.0-16a34a?style=flat-square" alt="Version 1.1.0">
  </a>
  <a href="LICENSE">
    <img src="https://img.shields.io/badge/license-Apache--2.0-blue?style=flat-square" alt="License: Apache-2.0">
  </a>
  <a href="https://www.postgresql.org/">
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    <img src="https://img.shields.io/github/last-commit/evokoa/pggraph?style=flat-square&logo=github&label=last%20commit" alt="Last commit">
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pgGraph is a PostgreSQL extension for running graph search, traversal, shortest
path, and relationship queries directly against ordinary PostgreSQL tables.

Your tables stay the source of truth. pgGraph builds a derived graph index and
lets you query it from SQL using functions in the `graph` schema.

> [!TIP]
> **Looking for a managed version?** We have launched a managed version of pgGraph on [polygres.com](https://polygres.com) for full high performance GraphRAG on Postgres.


## Why pgGraph?

PostgreSQL is great at relational queries, but graph-style questions often
require custom recursive SQL for each schema:

- “Find records related to Alice within 2 hops.”
- “Find the shortest path between this person and this company.”
- “Search nodes across registered tables.”

pgGraph adds graph queries on top of your existing PostgreSQL tables, without
requiring a separate graph database, graph-specific storage system, or a new
query language.

## Quickstart

The repository quickstart builds a disposable PostgreSQL 17 image:

```bash
git clone https://github.com/evokoa/pggraph.git
cd pggraph
scripts/quickstart.sh
```

The signed multi-architecture release image is
`ghcr.io/evokoa/pggraph:1.1.0`. Verify its published digest before deployment.

Verify the extensions are loaded (uses `psql` inside the container, so you
don't need a local PostgreSQL client):

```bash
docker exec pggraph psql -U postgres -d graph \
  -c "SELECT extname, extversion FROM pg_extension WHERE extname IN ('graph', 'pg_cron');"
```

If you have `psql` installed locally you can also connect directly:

```bash
psql -h localhost -U postgres -d graph
```

## Homebrew Installation

The [Evokoa Homebrew tap](https://github.com/Evokoa/homebrew-tap) is the
convenience channel for local PostgreSQL 17 extension installs.

```bash
brew tap Evokoa/tap
brew install pggraph
brew test pggraph
```

Create and verify the extension in a local database:

```bash
brew services start postgresql@17
psql -d postgres -c "CREATE EXTENSION graph;"
psql -d postgres -c "SELECT extname, extversion FROM pg_extension WHERE extname = 'graph';"
```

The formula installs pgGraph 1.1.0 from the signed release bundle.

To build from source or run the full interactive demo instead, use the included
quickstart script. It starts a disposable Docker-backed PostgreSQL database,
installs pgGraph, creates two normal PostgreSQL tables, discovers the foreign
key relationship, builds the graph, and runs example queries. If the image's
scheduled maintenance is already active, the demo waits for that bounded
operation to finish before building instead of failing with a transient lock.

You need Docker or Docker Desktop installed and running:

- macOS: install Docker Desktop.
- Windows: install Docker Desktop with WSL2 enabled, then run the script from
  WSL2 or Git Bash.
- Linux: install Docker Engine and the Docker Compose plugin.

```bash
git clone https://github.com/evokoa/pggraph.git
cd pggraph

# run the full quickstart demo
scripts/quickstart.sh

# install into existing Postgres Docker container
scripts/quickstart.sh docker my-postgres 17 appdb postgres

# source build/install with pgrx into local PostgreSQL
scripts/quickstart.sh pgrx

# start Streamlit playground with a preset dataset and mode (csr|mutable)
scripts/quickstart.sh playground panama csr
scripts/quickstart.sh playground panama mutable
```

Supported modes:

- `quickstart` / `demo`: build and start the Docker Postgres service, load demo
  data, and run example graph queries. This is the default mode.
- `setup`: build and start Postgres with pgGraph installed, but do not load the
  sample graph.
- `psql`: build and start Postgres, prepare demo data, then open `psql`.
- `docker CONTAINER [PG_MAJOR] [DB_NAME] [DB_USER]`: install pgGraph into an
  existing running Postgres Docker container via
  `scripts/install_into_docker_postgres.sh`.
- `pgrx [PG_MAJOR]`: build and install pgGraph into a local PostgreSQL using
  `cargo pgrx install`.
- `playground [panama|ldbc] [csr|mutable]`: start the Streamlit playground
  using a preset dataset and projection mode.
- `clean`: stop the Compose database and remove its volume.

The script works on macOS and Linux from a normal terminal, and on Windows from
WSL2 or Git Bash with Docker Desktop. It is not a native PowerShell or Command
Prompt script.

Docker images are published for PostgreSQL 14 through 18. Tags without a
PostgreSQL major, such as `1.1.0` and `latest`, use the default PostgreSQL 17
image.
PostgreSQL 13 is no longer an official support target after upstream EOL, though
the legacy `pg13` pgrx feature remains available on a best-effort basis. The
PostgreSQL major version of the extension package must match the target server.

## PGXN Source Installation

PGXN provides the verified source ZIP from the signed 1.1.0 release bundle.
Because pgGraph is a Rust/pgrx extension, building from source requires the Rust
toolchain.

### Prerequisites

- PostgreSQL development headers and `pg_config`
- Rust toolchain (`1.96`, pinned by `graph/rust-toolchain.toml`)
- `cargo-pgrx` 0.19.1

### Install with pgxn-client

```bash
cargo install cargo-pgrx --version 0.19.1 --locked
# Register the installed PostgreSQL with pgrx (auto-detects the major):
PG_MAJOR=$(pg_config --version | sed -E 's/[^0-9]*([0-9]+).*/\1/')
cargo pgrx init --pg${PG_MAJOR}="$(which pg_config)"
pgxn install pgGraph
```

### Manual source install

```bash
git clone https://github.com/evokoa/pggraph.git
cd pggraph
make install # may need sudo
psql -d postgres -c "CREATE EXTENSION graph;"
```

If you have multiple PostgreSQL installations, set `PG_CONFIG` to the target
server's `pg_config`, then re-run the installation:

```bash
export PG_CONFIG=/usr/lib/postgresql/17/bin/pg_config
make install
```

If `sudo` is needed for `make install`, preserve `PG_CONFIG`:

```bash
sudo --preserve-env=PG_CONFIG make install
```

If compilation fails with `fatal error: postgres.h: No such file or directory`,
install the PostgreSQL server development package for the target PostgreSQL
major, such as `postgresql-server-dev-17` on Ubuntu or Debian.

> **Note:** The PGXN distribution name is `pgGraph` but the PostgreSQL extension
> name is `graph`. Use `CREATE EXTENSION graph;` after installation.

## Documentation
More information is available in the pgGraph docs:

**[Overview](https://docs.evokoa.com/pggraph/user_guide)** ·
**[Quickstart](https://docs.evokoa.com/pggraph/quickstart)** ·
**[Installation](https://docs.evokoa.com/pggraph/user_guide/installation)** ·
**[Playground](https://docs.evokoa.com/pggraph/user_guide/playground)** ·
**[Querying](https://docs.evokoa.com/pggraph/user_guide/querying)** ·
**[SQL API](https://docs.evokoa.com/pggraph/user_guide/api-reference)**

## pgGraph: High-Speed Graph Execution Inside PostgreSQL

pgGraph is not "Postgres plus graph syntax." It is a cache-friendly graph
execution layer for data that already lives in your ordinary relational tables.

The core idea is simple but powerful: keep PostgreSQL as your system of record,
but build a highly optimized, read-heavy graph runtime from that relational
metadata. The result is closer to a rebuildable graph index than a graph
database: it is built from Postgres tables, operated with Postgres controls,
and optimized for repeated bounded traversal over known topology.

### The Tech: Why It's So Fast

Graph traversals usually die on recursive SQL queries or endless joins. pgGraph
bypasses this by compiling your relational data into a specialized memory
structure.

- **O(1) adjacency via CSR.** `graph.build()` compiles your relationships into
  forward and reverse compressed sparse row (CSR) edge stores. A node's
  neighbors are stored as a contiguous array slice. Instead of rediscovering
  relationships via SQL, traversals are executed as raw, graph-native memory
  scans.
- **A tight traversal loop.** SQL-facing calls resolve coordinates, labels,
  filters, and tenant scopes before entering the traversal loop. Once inside,
  the engine streams CSR neighbors, checking compact `u8` edge-label IDs,
  typed `FilterIndex` values, tenant bitmaps, active bits, and sync overlays.
- **Read-only artifact mapping.** Persisted `.pggraph` artifacts are written
  atomically. When a new Postgres backend spins up, it validates the artifact
  and copies it into a backend-local anonymous mapping before exposing immutable
  forward graph arrays and the resolution index through read-only views. The
  private snapshot prevents a concurrent write or truncation of the source file
  from invalidating live Rust references. It also means each backend that loads
  a graph retains approximately one artifact-sized private snapshot; base graph
  pages are not shared across backends through the operating system page cache.
  This is not a replacement for PostgreSQL's buffer pool: PostgreSQL remains
  responsible for table storage, WAL, MVCC, durability, and crash recovery,
  while pgGraph's artifact is derived state that can be rebuilt from source
  tables.
- **Predictable and safe.** Unbounded graph expansion can crash a database.
  pgGraph includes explicit circuit breakers: depth limits, visited-node
  tracking, frontier limits, pagination, and strict OOM/memory safeguards.

### PostgreSQL Remains Authoritative

Your application data does not move. Source tables, constraints, indexes, ACLs,
RLS, backups, and app writes remain 100% standard PostgreSQL concerns.

pgGraph is strictly derived state. You run the algorithms over internal node
indexes, and the engine returns source table coordinates or hydrates the raw
PostgreSQL rows on the fly. Build, sync, vacuum, and maintenance operations are
fully visible and SQL-callable.

### How pgGraph Compares

#### vs. Apache AGE: Execution Layer vs. Storage Layer

Apache AGE is a property graph database inside Postgres. It uses graph
namespaces, vertex and edge tables, `agtype`, and openCypher.

pgGraph does not ask you to move your data or learn Cypher. You keep your
existing schema and accelerate it with SQL functions like `graph.search()` and
`graph.shortest_path()`. Use AGE for a dedicated property graph model; use
pgGraph to add bounded, high-speed graph traversal to an existing relational
schema.

#### vs. PostgreSQL 19 SQL/PGQ

SQL:2023 and PostgreSQL 19 introduce `CREATE PROPERTY GRAPH`, `GRAPH_TABLE`,
and standard graph pattern matching backed by PostgreSQL's planner and
optimizer — the same engine that makes PostgreSQL's relational queries strong.

pgGraph operates at a different layer. SQL/PGQ expresses graph patterns and lets
the optimizer choose how to execute them. pgGraph precomputes CSR adjacency
stores and rebuildable artifacts for workloads that repeatedly traverse the same
topology with bounded depth, path limits, filters, tenants, and application
pagination. The pgGraph 1.0 PostgreSQL 14–18 contract does not expose SQL/PGQ.
PostgreSQL 19 integration is tracked separately on the public roadmap.

## Community

pgGraph is built by [Evokoa](https://evokoa.com).
Follow the project through
the links at the top of this README.

## License

Apache-2.0. See [LICENSE](LICENSE).
