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Business productivity ⇄ Database

GitHub to Google Cloud SQL integration — real-time, two-way sync

Keep GitHub and Google Cloud SQL 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 Google Cloud SQL

Mirror GitHub's data into Google Cloud SQL 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 Google Cloud SQL.

Stacksync mirrors Releases, Workflow runs (Actions), Organizations and Teams, Users from GitHub into Schemas, Tables, Rows, Views in Google Cloud SQL 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 Sync organization and team membership with an identity or HR system to automate access reviews and offboarding.
  • 02 Create GitHub issues automatically from records written elsewhere, such as bug reports logged in a CRM case object.
  • 03 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
  • 04 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.

Common sync patterns

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 Google Cloud SQL; join them, index them, and use them in application logic without touching the vendor API.

Automate GitHub from your codebase

Write to the synced tables in Google Cloud SQL and Stacksync propagates the change into GitHub, replacing custom integration code.

What you can sync between GitHub and Google Cloud SQL

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 Google Cloud SQL objects How this pairing syncs
Organizations and Teams Membership data synced with identity systems and HR directories for access reviews. Tables Mapped directly to sync targets; schema changes can be propagated. Organizations and Teams is specific to GitHub and Tables to Google Cloud SQL — each maps to any object or custom field on the other side.
Users Author and assignee identities matched to internal directories. Rows Read and written by primary key during each sync cycle. Users is specific to GitHub and Rows to Google Cloud SQL — 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. Views Read-only sources for shaping data before syncing it out. Labels and Milestones is specific to GitHub and Views to Google Cloud SQL — 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. Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. Repositories is specific to GitHub and Transaction logs to Google Cloud SQL — 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. Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. Issues is specific to GitHub and Instances to Google Cloud SQL — 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. Databases Scope the tables included in a sync configuration. Pull Requests is specific to GitHub and Databases to Google Cloud SQL — each maps to any object or custom field on the other side.

How changes propagate between GitHub and Google Cloud SQL

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 Google Cloud SQL 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 Google Cloud SQL as a row-level write, with types converted between the two schemas.

Google Cloud SQL GitHub Sub-second propagation

DetectionChanges in Google Cloud SQL are captured at the source via change data capture — no polling loop against its API. Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking.

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.
  • Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with GitHub ⇄ Google Cloud SQL

Connect GitHub and Google Cloud SQL for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every GitHub–Google Cloud SQL connection.

Real-time

Two-way sync

Changes in GitHub or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever GitHub or Google Cloud SQL 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 Google Cloud SQL record.

Observability

Monitoring

Track your GitHub ⇄ Google Cloud SQL 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 Google Cloud SQL.

How the GitHub and Google Cloud SQL 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.

Google Cloud SQL

Integration surface
Native SQL wire protocols (MySQL, PostgreSQL, SQL Server) plus a REST admin API for instance management
Authentication
Database credentials; IAM database authentication is available for MySQL and PostgreSQL
Change detection
Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback
Capabilities
read · write · CDC
Rate limits
Constrained by instance size and connection limits rather than API quotas.
How it works

How to connect GitHub to Google Cloud SQL — 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 Google Cloud SQL 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
    Google Cloud SQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the GitHub and Google Cloud SQL 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 ⇄ Google Cloud SQL
    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 Google Cloud SQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

GitHub and Google Cloud SQL 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 386 integrations available for GitHub and Google Cloud SQL.

Popular · 8 of 386
All GitHub integrations All Google Cloud SQL integrations Browse all integrations
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