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PostgreSQL
+
Bruin

PostgreSQL + Bruin

SourceDestination

Ingest data from PostgreSQL or push enriched data back — with quality checks, lineage, and scheduling. Defined in YAML, version-controlled in Git.

For business teams

What you get

  • Real-time warehouse sync

    PostgreSQL tables replicate to your warehouse continuously. Analytics teams work with fresh data, not yesterday's export.

  • Catch issues at the source

    Quality checks validate PostgreSQL data as it replicates. Null IDs, duplicate records, and schema drift get caught early.

  • Multi-source joins

    Combine PostgreSQL with SaaS data, APIs, and other databases in your warehouse. One Bruin pipeline handles it all.

  • No untracked scripts

    Replication is defined in YAML, reviewed in PRs, and deployed with CI/CD. No more mystery cron jobs.

For data & engineering teams

How it works

  • CDC with merge strategy

    Bruin handles change data capture from PostgreSQL with deduplication. Schema changes are detected and handled automatically.

  • YAML-defined, Git-versioned

    Your PostgreSQL replication is a YAML file. Review in PRs, deploy with CI/CD. No more untracked database scripts.

  • Row-level quality checks

    Validate primary keys, foreign keys, and referential integrity on every sync. Catch corruption at the source.

  • Multi-source pipelines

    Combine PostgreSQL with SaaS APIs and other databases in one pipeline. Bruin resolves cross-source dependencies.

Before you start

PostgreSQL server accessible from your network
Database user with appropriate permissions
pg_hba.conf configured to allow connections
Firewall rules allowing port 5432 (or custom port)

Step 1

Add your PostgreSQL connection

PostgreSQL connection using standard connection string format. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

  • usernameDatabase user
  • passwordUser password
  • hostDatabase server hostname or IP
  • portServer port (default 5432)
  • databaseDatabase name
  • sslmodeSSL mode (disable, require, verify-ca, verify-full)
connections:
  postgresql:
    type: postgresql
    uri: "postgresql://username:password@host:port/database?sslmode=disable"

Step 2

Create your pipeline

Define a YAML asset that tells Bruin what to pull from PostgreSQL and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.

Available tables

public.userspublic.orderspublic.productsanalytics.events
name: raw.postgresql_public.users
type: ingestr

parameters:
  source_connection: postgresql
  source_table: 'public.users'
  destination: bigquery

Step 3

Add quality checks

Add column-level and custom SQL checks to your PostgreSQL data. If a check fails, the pipeline stops — bad data never reaches downstream models or dashboards.

Validate row counts are within expected range
Ensure primary keys are unique and not null
Catch schema drift with freshness checks
columns:
  - name: id
    checks:
      - name: not_null
      - name: unique
  - name: created_at
    checks:
      - name: not_null

custom_checks:
  - name: row count within expected range
    query: |
      SELECT COUNT(*) BETWEEN 1 AND 10000000
      FROM raw.postgresql_public.users

Step 4

Run it

One command. Bruin connects to PostgreSQL, pulls data incrementally, runs your quality checks, and lands clean data in your warehouse. If a check fails, the pipeline stops — bad data never reaches downstream.

Backfill historical data with --start-date
Schedule with cron or trigger from CI/CD
Full lineage from PostgreSQL to your dashboards
$ bruin run .
Running pipeline...

  postgresql_public.users
    ✓ Fetched 2,847 new records
    ✓ Quality: campaign_id not_null     PASSED
    ✓ Quality: spend not_null           PASSED
    ✓ Quality: no negative ad spend     PASSED
    ✓ Loaded into bigquery

  Completed in 12s

Ready to connect PostgreSQL?

Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.