Real-time
Two-way sync
Changes in Atlassian or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Database
Atlassian to Postgres Heroku integration — real-time, two-way sync
Keep Atlassian and Postgres Heroku 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 Postgres Heroku
Mirror Atlassian's data into Postgres Heroku 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 Postgres Heroku.
Stacksync mirrors Attachments, Custom Fields, Workflows and Statuses, Users and Groups from Atlassian into Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases in Postgres Heroku 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
- Keep Jira and a second tracker (for example a customer's Jira instance) aligned during co-delivery projects.
- Sync Confluence page metadata into a knowledge index so other tools can link to current documentation.
- Sync Heroku Postgres into a warehouse for reporting without running ETL dynos
- Keep several Heroku app databases aligned with one system of record
React to changes as they happen
Updates in Atlassian arrive as row changes in Postgres Heroku, 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.
Read Atlassian with a query
Records from Atlassian are ordinary rows in Postgres Heroku; join them, index them, and use them in application logic without touching the vendor API.
What you can sync between Atlassian and Postgres Heroku
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 | Postgres Heroku objects | |
|---|---|---|
| Custom Fields Instance-specific fields (customfield IDs) that carry most business-specific data in syncs. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. | |
| Workflows and Statuses Status transitions mapped to stages in the paired system. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | |
| Users and Groups Assignees and reporters matched to identities in other tools. | Sequences Generate surrogate keys for rows created by inbound syncs. | |
| Confluence Pages Documentation content readable and writable through the Confluence REST API. | Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | |
| Confluence Spaces Namespaces that scope page syncs and permissions. | Tables Standard Postgres tables; the primary two-way sync target for app data. | |
| Jira Issues The central work item, synced two-way with CRMs, support desks, and other trackers. | Views Read-side projections exposed to outbound syncs. |
What ships with Atlassian ⇄ Postgres Heroku
Connect Atlassian and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Atlassian–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Atlassian or Postgres Heroku 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 Postgres Heroku record.
Observability
Monitoring
Track your Atlassian ⇄ Postgres Heroku 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 Postgres Heroku.
How the Atlassian and Postgres Heroku 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
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works
How to connect Atlassian to Postgres Heroku — 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 Postgres Heroku 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
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Atlassian and Postgres Heroku 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 ⇄ Postgres HerokuCustomers 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 Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Atlassian and Postgres Heroku integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Atlassian and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Atlassian's Custom Fields and Workflows and Statuses), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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 Postgres Heroku records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Atlassian and Postgres Heroku connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Atlassian–Postgres Heroku integration in-house.
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Yes — Stacksync ships production-grade connectors for both Atlassian and Postgres Heroku. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Atlassian: Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill. On Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. 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: Attachments, Custom Fields, Workflows and Statuses, Users and Groups, plus custom fields where Atlassian exposes them. On the Postgres Heroku side: Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases. Stacksync auto-detects both schemas and converts types between the two systems.
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 Postgres Heroku.
Popular · 8 of 386
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Atlassian ⇄ AWS Aurora PostgreSQL -
Atlassian ⇄ MongoDB -
Atlassian ⇄ CockroachDB -
Atlassian ⇄ Google AlloyDB -
Postgres Heroku ⇄ GitHub -
Postgres Heroku ⇄ Braze -
Postgres Heroku ⇄ ConnectWise -
Postgres Heroku ⇄ Aviato
No integrations match .
