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Business productivity ⇄ Database

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

Keep Atlassian 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 Atlassian and Google Cloud SQL

Mirror Atlassian'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 Atlassian 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 Jira Issues, Jira Projects, Boards and Sprints, Issue Comments from Atlassian into Views, Transaction logs, Instances, Databases 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 Atlassian, so the tool and the database never disagree.

Common use cases

  • Mirror Jira projects into a SQL database for engineering throughput and SLA reporting.
  • Create Jira issues from records in other systems, such as onboarding tasks generated from a closed-won CRM deal.
  • Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
  • Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.

Automate Atlassian from your codebase

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

React to changes as they happen

Updates in Atlassian arrive as row changes in Google Cloud SQL, 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 Atlassian 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.

Atlassian objects Google Cloud SQL objects
Boards and Sprints Agile structures read to report on sprint contents and status. Tables Mapped directly to sync targets; schema changes can be propagated.
Issue Comments Threaded discussion synced into linked tickets in external systems. Rows Read and written by primary key during each sync cycle.
Attachments Files on issues mirrored to paired records where needed. Views Read-only sources for shaping data before syncing it out.
Custom Fields Instance-specific fields (customfield IDs) that carry most business-specific data in syncs. Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture.
Workflows and Statuses Status transitions mapped to stages in the paired system. Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to.
Users and Groups Assignees and reporters matched to identities in other tools. Databases Scope the tables included in a sync configuration.
What ships with Atlassian ⇄ Google Cloud SQL

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

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

Real-time

Two-way sync

Changes in Atlassian 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 Atlassian 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 Atlassian or Google Cloud SQL record.

Observability

Monitoring

Track your Atlassian ⇄ 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 Atlassian and Google Cloud SQL.

How the Atlassian and Google Cloud SQL connectors work

Atlassian

Integration surface
REST APIs per product (Jira Cloud and Confluence Cloud)
Authentication
OAuth 2.0 (3LO) for apps or API tokens with basic auth for scripts
Change detection
Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill
Capabilities
read · write · webhooks

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 Atlassian 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 Atlassian 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
    Atlassian connected
    Google Cloud SQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Atlassian and Google Cloud SQL integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 Atlassian and Google Cloud SQL.

Popular · 8 of 386
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