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Database ⇄ Business productivity

AWS Aurora PostgreSQL to GitHub integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL and GitHub 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 AWS Aurora PostgreSQL and GitHub

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

Teams connect GitHub to AWS Aurora PostgreSQL to analyze engineering activity with SQL. Issues, Pull Requests, and Workflow runs sync into Aurora tables where they can be joined with other operational data and exposed through views for engineering dashboards.

Stacksync mirrors Commits, Releases, Workflow runs (Actions), Organizations and Teams from GitHub into Replication slots and publications, Databases and schemas, Tables, Rows in AWS Aurora PostgreSQL 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 Query Issues and Pull Requests across all Repositories from one PostgreSQL schema.
  • 02 Build materialized views over Workflow runs to monitor CI cost and flakiness.
  • 03 Correlate Releases with incident or deployment tables already stored in Aurora.
  • 04 Mirror repository, PR, and workflow-run data into a Postgres database for engineering-metrics reporting.

Common sync patterns

Engineering metrics store

Pull Requests and Commits replicate into Aurora PostgreSQL rows for cycle-time and review analytics.

CI health tracking

Workflow runs (Actions) sync to Aurora tables so failure rates are queryable per repository.

Release audit trail

Releases and Issues land in Aurora with primary keys enforced for compliance reporting.

What you can sync between AWS Aurora PostgreSQL and GitHub

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.

AWS Aurora PostgreSQL objects GitHub objects How this pairing syncs
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. Issues Synced two-way with project trackers and support tools, including labels and assignees. Columns is specific to AWS Aurora PostgreSQL and Issues to GitHub — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Pull Requests Review state, status checks, and merge status feed engineering dashboards and workflow tools. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Pull Requests to GitHub — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Commits Read-only history used to link code activity to tickets and releases. Views and materialized views is specific to AWS Aurora PostgreSQL and Commits to GitHub — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Releases Tagged versions synced into changelogs, CRMs, or customer-notification systems. Foreign keys is specific to AWS Aurora PostgreSQL and Releases to GitHub — each maps to any object or custom field on the other side.
Replication slots and publications The logical replication objects that power log-based CDC. Workflow runs (Actions) CI results synced into incident and reporting systems. Replication slots and publications is specific to AWS Aurora PostgreSQL and Workflow runs (Actions) to GitHub — each maps to any object or custom field on the other side.
Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. Organizations and Teams Membership data synced with identity systems and HR directories for access reviews. Databases and schemas is specific to AWS Aurora PostgreSQL and Organizations and Teams to GitHub — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL and GitHub

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.

AWS Aurora PostgreSQL GitHub Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

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

GitHub AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • GitHub: Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.
What ships with AWS Aurora PostgreSQL ⇄ GitHub

Connect AWS Aurora PostgreSQL and GitHub for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–GitHub connection.

Real-time

Two-way sync

Changes in AWS Aurora PostgreSQL or GitHub instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL or GitHub 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 AWS Aurora PostgreSQL or GitHub record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ GitHub sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and GitHub.

How the AWS Aurora PostgreSQL and GitHub connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
Capabilities
read · write · CDC

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.
How it works

How to connect AWS Aurora PostgreSQL to GitHub — 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 AWS Aurora PostgreSQL and GitHub 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
    AWS Aurora PostgreSQL connected
    GitHub connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL and GitHub 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 · AWS Aurora PostgreSQL ⇄ GitHub
    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
    AWS Aurora PostgreSQL GitHub
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora PostgreSQL and GitHub 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 403 integrations available for AWS Aurora PostgreSQL and GitHub.

Popular · 7 of 403
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