Real-time
Two-way sync
Changes in Atlassian or AWS Aurora PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Database
Atlassian to AWS Aurora PostgreSQL integration — real-time, two-way sync
Keep Atlassian and AWS Aurora PostgreSQL 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Atlassian and AWS Aurora PostgreSQL
Mirror Atlassian'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 sync Atlassian with AWS Aurora PostgreSQL to expose Jira as a relational surface their applications and analysts already know. Jira Issues, Issue Comments, and Custom Fields map to Tables and Rows in Aurora PostgreSQL schemas, with writes flowing back to Jira. Views and materialized views turn raw Issue data into stable reporting layers.
Stacksync mirrors Custom Fields, Workflows and Statuses, Users and Groups, Confluence Pages from Atlassian into Foreign keys, Replication slots and publications, Databases and schemas, Tables 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 Atlassian, so the tool and the database never disagree.
Common use cases
- 01 Power internal tools that read and write Jira Issues through standard PostgreSQL Rows.
- 02 Enforce data quality on incoming Issue data using Postgres constraints before it reaches reports.
- 03 Keep Issue Comments queryable in SQL for audit and support analysis.
- 04 Keep Jira and a second tracker (for example a customer's Jira instance) aligned during co-delivery projects.
Common sync patterns
Issues as relational data
Jira Issues and Custom Fields sync into Aurora PostgreSQL Tables with Primary keys and constraints preserving referential integrity.
Write-back from Postgres
inserting or updating Rows creates or updates Jira Issues directly from application code.
Materialized sprint views
Boards and Sprints data feeds Views and materialized views for low-latency delivery reporting.
What you can sync between Atlassian and AWS Aurora PostgreSQL
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 PostgreSQL objects | How this pairing syncs | |
|---|---|---|---|
| Users and Groups Assignees and reporters matched to identities in other tools. | Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | Users and Groups is specific to Atlassian and Columns to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Confluence Pages Documentation content readable and writable through the Confluence REST API. | Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. | Confluence Pages is specific to Atlassian and Primary keys and constraints to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Confluence Spaces Namespaces that scope page syncs and permissions. | Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. | Confluence Spaces is specific to Atlassian and Views and materialized views to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Jira Issues The central work item, synced two-way with CRMs, support desks, and other trackers. | Foreign keys Relationship metadata that syncs can translate into object references elsewhere. | Jira Issues is specific to Atlassian and Foreign keys to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Jira Projects Containers that scope issues, workflows, and permissions for a sync. | Replication slots and publications The logical replication objects that power log-based CDC. | Jira Projects is specific to Atlassian and Replication slots and publications to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. | |
| Boards and Sprints Agile structures read to report on sprint contents and status. | Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | Boards and Sprints is specific to Atlassian and Databases and schemas to AWS Aurora PostgreSQL — each maps to any object or custom field on the other side. |
How changes propagate between Atlassian and AWS Aurora PostgreSQL
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.
Atlassian AWS Aurora PostgreSQL Sub-second propagation
DetectionAtlassian notifies Stacksync of record changes through webhook events. Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill.
DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.
AWS Aurora PostgreSQL Atlassian 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 Atlassian through its API, with automatic retries and rate-limit backoff.
What ships with Atlassian ⇄ AWS Aurora PostgreSQL
Connect Atlassian and AWS Aurora PostgreSQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Atlassian–AWS Aurora PostgreSQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Atlassian or AWS Aurora PostgreSQL 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 PostgreSQL record.
Observability
Monitoring
Track your Atlassian ⇄ AWS Aurora PostgreSQL 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 PostgreSQL.
How the Atlassian and AWS Aurora PostgreSQL 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 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
How it works
How to connect Atlassian to AWS Aurora PostgreSQL — 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 PostgreSQL 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 PostgreSQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Atlassian and AWS Aurora PostgreSQL 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 PostgreSQLCustomers 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 PostgreSQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Atlassian and AWS Aurora PostgreSQL integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Atlassian and AWS Aurora PostgreSQL: authenticate both systems, choose the objects to sync (such as Atlassian's Users and Groups and Confluence Pages), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Atlassian and AWS Aurora PostgreSQL records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Atlassian and AWS Aurora PostgreSQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Atlassian–AWS Aurora PostgreSQL integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Atlassian and AWS Aurora PostgreSQL. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Atlassian: Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill. On AWS Aurora PostgreSQL: Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the Atlassian side: Custom Fields, Workflows and Statuses, Users and Groups, Confluence Pages, plus custom fields where Atlassian exposes them. On the AWS Aurora PostgreSQL side: Foreign keys, Replication slots and publications, Databases and schemas, Tables. Stacksync auto-detects both schemas and converts types between the two systems.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 390 integrations available for Atlassian and AWS Aurora PostgreSQL.
Popular · 7 of 390
-
Atlassian ⇄ MySQL -
Atlassian ⇄ MariaDB -
Atlassian ⇄ SQL Server -
Atlassian ⇄ Postgres Heroku -
AWS Aurora PostgreSQL ⇄ Orderful -
AWS Aurora PostgreSQL ⇄ ServiceNow -
AWS Aurora PostgreSQL ⇄ Slack
No integrations match .
