Real-time
Two-way sync
Changes in Atlassian or AWS Aurora MySQL instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Database
Atlassian to AWS Aurora MySQL integration — real-time, two-way sync
Keep Atlassian and AWS Aurora MySQL 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 AWS Aurora MySQL
Mirror Atlassian's data into AWS Aurora MySQL 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 AWS Aurora MySQL.
Stacksync mirrors Jira Projects, Boards and Sprints, Issue Comments, Attachments from Atlassian into Foreign keys, Stored procedures and triggers, Databases (schemas), Tables in AWS Aurora MySQL 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
- Sync Confluence page metadata into a knowledge index so other tools can link to current documentation.
- Mirror Jira projects into a SQL database for engineering throughput and SLA reporting.
- Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.
- Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
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 Atlassian with a query
Records from Atlassian are ordinary rows in AWS Aurora MySQL; join them, index them, and use them in application logic without touching the vendor API.
Automate Atlassian from your codebase
Write to the synced tables in AWS Aurora MySQL and Stacksync propagates the change into Atlassian, replacing custom integration code.
What you can sync between Atlassian and AWS Aurora MySQL
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 | AWS Aurora MySQL objects | |
|---|---|---|
| Confluence Spaces Namespaces that scope page syncs and permissions. | Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | |
| Jira Issues The central work item, synced two-way with CRMs, support desks, and other trackers. | Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | |
| Jira Projects Containers that scope issues, workflows, and permissions for a sync. | Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | |
| Boards and Sprints Agile structures read to report on sprint contents and status. | Columns MySQL data types are mapped to the paired system's field types during schema setup. | |
| Issue Comments Threaded discussion synced into linked tickets in external systems. | Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | |
| Attachments Files on issues mirrored to paired records where needed. | Views Can serve as read-only sync sources for derived or filtered datasets. |
What ships with Atlassian ⇄ AWS Aurora MySQL
Connect Atlassian and AWS Aurora MySQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Atlassian–AWS Aurora MySQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Atlassian or AWS Aurora MySQL 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 AWS Aurora MySQL record.
Observability
Monitoring
Track your Atlassian ⇄ AWS Aurora MySQL 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 AWS Aurora MySQL.
How the Atlassian and AWS Aurora MySQL 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
AWS Aurora MySQL
- Integration surface
- SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
- Authentication
- Database credentials, optionally AWS IAM database authentication, over TLS
- Change detection
- Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
- Capabilities
- read · write · CDC
How it works
How to connect Atlassian to AWS Aurora MySQL — 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.
- 01
Connect your apps
Authenticate Atlassian and AWS Aurora MySQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Atlassian
connected
AWS Aurora MySQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Atlassian and AWS Aurora MySQL 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.
objects · Atlassian ⇄ AWS Aurora MySQLCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Atlassian AWS Aurora MySQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Atlassian and AWS Aurora MySQL integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Atlassian and AWS Aurora MySQL: authenticate both systems, choose the objects to sync (such as Atlassian's Confluence Spaces and Jira Issues), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Change detection on Atlassian: Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill. On AWS Aurora MySQL: Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Atlassian side: Jira Projects, Boards and Sprints, Issue Comments, Attachments, plus custom fields where Atlassian exposes them. On the AWS Aurora MySQL side: Foreign keys, Stored procedures and triggers, Databases (schemas), Tables. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Atlassian and AWS Aurora MySQL: One integration pattern for the whole stack; Read Atlassian with a query; Automate Atlassian from your codebase. Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.
-
Atlassian: REST APIs per product (Jira Cloud and Confluence Cloud). Authentication: OAuth 2.0 (3LO) for apps or API tokens with basic auth for scripts. AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Atlassian and AWS Aurora MySQL.
Popular · 8 of 386
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Atlassian ⇄ Airtable - Atlassian ⇄ AWS Aurora PostgreSQL
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Atlassian ⇄ MongoDB -
Atlassian ⇄ CockroachDB -
AWS Aurora MySQL ⇄ Resend - AWS Aurora MySQL ⇄ ServiceNow
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AWS Aurora MySQL ⇄ Slack -
AWS Aurora MySQL ⇄ Zendesk
No integrations match .
