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GitHub to Postgres Heroku integration — real-time, two-way sync

Keep GitHub and Postgres Heroku in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect GitHub and Postgres Heroku

Mirror GitHub's data into Postgres Heroku so your own code can read and write it like any other table, with changes flowing both ways in seconds.

Engineers integrate with tools like GitHub through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Postgres Heroku.

Stacksync mirrors Organizations and Teams, Users, Labels and Milestones, Repositories from GitHub into Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases in Postgres Heroku and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into GitHub, so the tool and the database never disagree.

Common use cases

  • 01 Mirror repository, PR, and workflow-run data into a Postgres database for engineering-metrics reporting.
  • 02 Sync organization and team membership with an identity or HR system to automate access reviews and offboarding.
  • 03 Sync Heroku Postgres into a warehouse for reporting without running ETL dynos
  • 04 Keep several Heroku app databases aligned with one system of record

Common sync patterns

React to changes as they happen

Updates in GitHub arrive as row changes in Postgres Heroku, so triggers, jobs, and services can respond in near real time.

One integration pattern for the whole stack

Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.

Read GitHub with a query

Records from GitHub are ordinary rows in Postgres Heroku; join them, index them, and use them in application logic without touching the vendor API.

What you can sync between GitHub and Postgres Heroku

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

GitHub objects Postgres Heroku objects How this pairing syncs
Users Author and assignee identities matched to internal directories. JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. Users is specific to GitHub and JSONB Columns to Postgres Heroku — each maps to any object or custom field on the other side.
Labels and Milestones Classification fields mapped to statuses and sprints in external trackers. Sequences Generate surrogate keys for rows created by inbound syncs. Labels and Milestones is specific to GitHub and Sequences to Postgres Heroku — each maps to any object or custom field on the other side.
Repositories Top-level containers whose metadata and settings syncs read to scope other objects. Follower Databases Heroku-managed read replicas usable as low-impact sync sources. Repositories is specific to GitHub and Follower Databases to Postgres Heroku — each maps to any object or custom field on the other side.
Issues Synced two-way with project trackers and support tools, including labels and assignees. Tables Standard Postgres tables; the primary two-way sync target for app data. Issues is specific to GitHub and Tables to Postgres Heroku — each maps to any object or custom field on the other side.
Pull Requests Review state, status checks, and merge status feed engineering dashboards and workflow tools. Views Read-side projections exposed to outbound syncs. Pull Requests is specific to GitHub and Views to Postgres Heroku — each maps to any object or custom field on the other side.
Commits Read-only history used to link code activity to tickets and releases. Materialized Views Precomputed result sets synced outward on refresh. Commits is specific to GitHub and Materialized Views to Postgres Heroku — each maps to any object or custom field on the other side.

How changes propagate between GitHub and Postgres Heroku

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

GitHub Postgres Heroku Sub-second propagation

DetectionGitHub notifies Stacksync of record changes through webhook events. Webhooks with a broad event catalog covering issues, pull requests, pushes, and releases.

DeliveryEach detected change is applied to Postgres Heroku as a row-level write, with types converted between the two schemas.

Postgres Heroku GitHub Interval-based propagation

DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.

DeliveryEach detected change is written to GitHub through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • GitHub: Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.
  • Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with GitHub ⇄ Postgres Heroku

Connect GitHub and Postgres Heroku for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every GitHub–Postgres Heroku connection.

Real-time

Two-way sync

Changes in GitHub or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever GitHub or Postgres Heroku data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single GitHub or Postgres Heroku record.

Observability

Monitoring

Track your GitHub ⇄ Postgres Heroku sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between GitHub and Postgres Heroku.

How the GitHub and Postgres Heroku connectors work

GitHub

Integration surface
REST API and GraphQL API
Authentication
OAuth 2.0, fine-grained personal access tokens, or GitHub App installation tokens
Change detection
Webhooks with a broad event catalog covering issues, pull requests, pushes, and releases; polling for backfill
Capabilities
read · write · webhooks
Rate limits
Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.

Postgres Heroku

Integration surface
SQL wire protocol (standard PostgreSQL)
Authentication
Database credentials from the Heroku DATABASE_URL config var; SSL required
Change detection
Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
Capabilities
read · write
Rate limits
No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works

How to connect GitHub to Postgres Heroku — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate GitHub and Postgres Heroku with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    GitHub connected
    Postgres Heroku connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the GitHub and Postgres Heroku objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · GitHub ⇄ Postgres Heroku
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    GitHub Postgres Heroku
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

GitHub and Postgres Heroku integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 399 integrations available for GitHub and Postgres Heroku.

Popular · 6 of 399
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