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Database ⇄ Business productivity

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

Keep Amazon Aurora 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 Amazon Aurora and GitHub

Mirror GitHub's data into Amazon Aurora 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 Amazon Aurora.

Stacksync mirrors Pull Requests, Commits, Releases, Workflow runs (Actions) from GitHub into Tables, Views, Materialized Views, Columns and Data Types in Amazon Aurora 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 Two-way sync between Aurora application tables and a CRM so product data and account data stay consistent.
  • 04 Stream row-level changes from Aurora into a warehouse for near-real-time analytics without batch exports.

Common sync patterns

Automate GitHub from your codebase

Write to the synced tables in Amazon Aurora and Stacksync propagates the change into GitHub, replacing custom integration code.

React to changes as they happen

Updates in GitHub arrive as row changes in Amazon Aurora, 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.

What you can sync between Amazon Aurora 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.

Amazon Aurora objects GitHub objects How this pairing syncs
Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. Pull Requests Review state, status checks, and merge status feed engineering dashboards and workflow tools. Materialized Views is specific to Amazon Aurora and Pull Requests to GitHub — each maps to any object or custom field on the other side.
Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. Commits Read-only history used to link code activity to tickets and releases. Columns and Data Types is specific to Amazon Aurora and Commits to GitHub — each maps to any object or custom field on the other side.
Primary and Foreign Keys Constraints used to identify records and preserve relational integrity in syncs. Releases Tagged versions synced into changelogs, CRMs, or customer-notification systems. Primary and Foreign Keys is specific to Amazon Aurora and Releases to GitHub — each maps to any object or custom field on the other side.
Read Replicas Reader endpoints that syncs can target to keep load off the writer. Workflow runs (Actions) CI results synced into incident and reporting systems. Read Replicas is specific to Amazon Aurora and Workflow runs (Actions) to GitHub — each maps to any object or custom field on the other side.
Databases Logical databases within a cluster that scope a sync connection. Organizations and Teams Membership data synced with identity systems and HR directories for access reviews. Databases is specific to Amazon Aurora and Organizations and Teams to GitHub — each maps to any object or custom field on the other side.
Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. Users Author and assignee identities matched to internal directories. Schemas is specific to Amazon Aurora and Users to GitHub — each maps to any object or custom field on the other side.

How changes propagate between Amazon Aurora 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.

Amazon Aurora GitHub Sub-second propagation

DetectionChanges in Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.

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

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

Rate-limit considerations

  • Amazon Aurora: No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits.
  • GitHub: Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.
What ships with Amazon Aurora ⇄ GitHub

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Aurora 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 Amazon Aurora or GitHub record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Amazon Aurora and GitHub connectors work

Amazon Aurora

Integration surface
MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits

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 Amazon Aurora 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 Amazon Aurora 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
    Amazon Aurora connected
    GitHub connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Amazon Aurora 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 385 integrations available for Amazon Aurora and GitHub.

Popular · 6 of 385
All Amazon Aurora integrations All GitHub integrations Browse all integrations
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