# Quickstart

This guide shows the fastest ways to try pgGraph in a disposable PostgreSQL 17
database, then walks through the SQL that creates a small graph and runs search,
traversal, and shortest-path queries.

Use this page for local evaluation. For in-depth installation, schema modeling,
and query semantics, use the linked user guide pages instead of treating this as
the full manual.

## Prerequisites

You need Docker or Docker Desktop installed and running:

| Platform | Requirement |
|---|---|
| macOS | Docker Desktop |
| Windows | Docker Desktop with WSL2 enabled; run commands from WSL2 or Git Bash |
| Linux | Docker Engine and the Docker Compose plugin |

The quickstart scripts are Bash scripts. They work from a macOS/Linux terminal,
or from WSL2/Git Bash on Windows. They are not native PowerShell or Command
Prompt scripts.

<Callout type="info">
  The root Docker image currently runs PostgreSQL 17. Package scripts can build
  extension artifacts for officially supported PostgreSQL 14 through 18 targets.
  PostgreSQL 13 has reached upstream EOL and is only best-effort through the
  legacy pgrx feature. The PostgreSQL major version of the extension package
  must match the target server. See
  [Installation](/user_guide/installation) for source builds, pgrx setup,
  package builds, and installation into existing servers.
</Callout>

## Get The Repository

Clone pgGraph and move into the repository:

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

## Fastest Path: Quickstart Script

From the repository root, run the included script:

```bash
scripts/quickstart.sh
```

The default command builds and starts the Docker-backed PostgreSQL database,
creates two ordinary PostgreSQL tables, discovers their foreign key
relationship, builds the graph, and prints example query results.

The script also has focused subcommands:

| Command | What it does |
|---|---|
| `scripts/quickstart.sh` | Run the full demo. Same as `scripts/quickstart.sh` `demo`. |
| `scripts/quickstart.sh` `setup` | Build and start PostgreSQL with pgGraph installed, without creating demo tables. |
| `scripts/quickstart.sh` `psql` | Build and start PostgreSQL, create and build the demo graph, then open `psql`. |
| `scripts/quickstart.sh` `clean` | Stop the Compose database and remove its disposable volume. |

Use `setup` when you want an empty scratch database with pgGraph installed. Use
`psql` when you want the sample graph created for interactive exploration.

## Other Local Paths

| Path | Use when | Start here |
|---|---|---|
| Quickstart script | You want the fastest local trial | `scripts/quickstart.sh` |
| Docker Compose scratch database | You want a disposable pgGraph database and will run SQL yourself | `docker compose up --build -d` |
| Streamlit playground | You want a browser SQL inspector with a real dataset | [Playground](/user_guide/playground) |
| Existing PostgreSQL Docker container | You already have a container to install into | [Installation](/user_guide/installation#install-into-an-existing-postgresql-container) |
| Source build with pgrx | You are developing pgGraph or building against local PostgreSQL headers | [Installation](/user_guide/installation) |

## Manual Docker Compose Flow

From the repository root:

```bash
docker compose up --build -d
docker compose exec postgres psql -U postgres -d graph
```

The Compose service builds the root Docker image and starts PostgreSQL with
pgGraph available. On a fresh Compose volume, the image also creates the
`pg_cron` extension and schedules `graph.run_scheduled_maintenance()` every five
minutes as `pggraph-maintenance`. Recreate the Compose volume after Docker init
SQL changes:

```bash
docker compose down -v
docker compose up --build -d
```

The rest of this page assumes you are inside that `psql` session.

## Create A Small Graph

Paste this whole block into `psql`:

```sql
CREATE EXTENSION IF NOT EXISTS graph;
SELECT graph.reset();

DROP TABLE IF EXISTS people CASCADE;
DROP TABLE IF EXISTS companies CASCADE;

CREATE TABLE companies (
  id text PRIMARY KEY,
  name text NOT NULL
);

CREATE TABLE people (
  id text PRIMARY KEY,
  name text NOT NULL,
  company_id text REFERENCES companies(id)
);

INSERT INTO companies VALUES
  ('c1', 'Acme Bank'),
  ('c2', 'Northwind Trading');

INSERT INTO people VALUES
  ('p1', 'Alice', 'c1'),
  ('p2', 'Bob', 'c1'),
  ('p3', 'Carol', 'c2');
```

## Register And Build

Use auto-discovery for schemas with primary keys and foreign keys:

```sql
SELECT * FROM graph.auto_discover('public');
```

`graph.auto_discover('public')` registers discovered source tables, discovers
foreign keys between them, and builds the graph.

If you want to limit discovery to specific tables, use
`graph.auto_discover_tables()`:

```sql
SELECT * FROM graph.auto_discover_tables(
  ARRAY['public.companies'::regclass, 'public.people'::regclass]
);
```

Confirm that pgGraph loaded nodes and edges:

```sql
SELECT node_count, edge_count, edge_types
FROM graph.status();
```

You should see three nodes and at least one edge type.

For composite keys, explicit labels, edge direction, weights, tenant columns,
filter columns, and other modeling details, see
[Schema Registration](/user_guide/schema-registration).

## Query

Search registered source-table columns:

```sql
SELECT node_table_name, node_id, node
FROM graph.search(
  'name',
  'Alice',
  table_filter := 'public.people'::regclass,
  mode := 'exact'
);
```

Traverse two hops from Alice:

```sql
SELECT depth, node_table_name, node_id, edge_path
FROM graph.traverse(
  'public.people'::regclass,
  'p1',
  2,
  hydrate := false
);
```

Find the shortest path from Alice to Acme Bank:

```sql
SELECT step, node_table_name, node_id, edge_label
FROM graph.shortest_path(
  'public.people'::regclass,
  'p1',
  'public.companies'::regclass,
  'c1',
  hydrate := false
);
```

The examples above return compact output. Remove `hydrate := false` when you
want hydrated node JSON in traversal and path results.

For the full query surface, including traversal specs, filters, workflow
wrappers, path reconstruction, weighted shortest paths, and connected
components, see [Querying](/user_guide/querying) and the
[SQL API Reference](/user_guide/api-reference).

## Manual Registration

Auto-discovery is the fastest start for primary-key and foreign-key schemas.
Manual registration gives more control over labels, direction, weights, tenant
columns, and search columns. This small example mirrors the graph above:

```sql
SELECT graph.reset();

SELECT graph.add_table(
  'public.people'::regclass,
  id_column := 'id',
  columns := ARRAY['name']
);

SELECT graph.add_table(
  'public.companies'::regclass,
  id_column := 'id',
  columns := ARRAY['name']
);

SELECT graph.add_edge(
  from_table := 'public.people'::regclass,
  from_column := 'company_id',
  to_table := 'public.companies'::regclass,
  to_column := 'id',
  label := 'works_at',
  bidirectional := true
);

SELECT * FROM graph.build();
```

For production schemas, prefer the full
[Schema Registration](/user_guide/schema-registration) guide before finalizing
labels, weights, filters, sync behavior, or tenant boundaries.

## Clean Up

Exit `psql`, then stop and remove the disposable database:

```bash
docker compose down -v
```

If you used the quickstart script, the equivalent cleanup command is:

```bash
scripts/quickstart.sh clean
```

## Next Steps

- [Playground](/user_guide/playground) to open a SQL inspector with a prepared
  real dataset.
- [Installation](/user_guide/installation) for source builds, pgrx, and
  container installation.
- [Schema Registration](/user_guide/schema-registration) to model tables,
  edges, weights, labels, filters, and tenants.
- [Querying](/user_guide/querying) for search, traversal, workflow wrappers,
  paths, filters, and components.
- [Security](/user_guide/administration-and-security) before exposing graph
  functions to application roles.
