Real-time
Two-way sync
Changes in Atlassian or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Data warehouse
Atlassian to Cloudera Data Platform integration — real-time, two-way sync
Keep Atlassian and Cloudera Data Platform in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Atlassian and Cloudera Data Platform
Get the data locked inside Atlassian into Cloudera Data Platform as live tables, and send results back where Atlassian can use them, without writing a pipeline.
Whatever Atlassian is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
Stacksync syncs Boards and Sprints, Issue Comments, Attachments, Custom Fields from Atlassian into tables in Cloudera Data Platform continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Cloudera Data Platform can also be written back into fields in Atlassian where the tool can use them.
Common use cases
- 01 Create Jira issues from records in other systems, such as onboarding tasks generated from a closed-won CRM deal.
- 02 Keep Jira and a second tracker (for example a customer's Jira instance) aligned during co-delivery projects.
- 03 Publish CRM or ERP records into CDP so enterprise analytics runs alongside existing data lake workloads.
- 04 Consolidate tables from on-prem and cloud CDP environments into a single cloud warehouse target.
Common sync patterns
History that outlives the tool
A continuously synced copy in Cloudera Data Platform preserves a queryable record even as data ages out of Atlassian or gets changed inside it.
Analytics on Atlassian's data
Records and events from Atlassian land in Cloudera Data Platform as queryable tables, current within seconds and ready to join with the rest of the warehouse.
Cross-tool reporting
Combine Atlassian's data with data from every other synced system to answer questions no single tool can.
What you can sync between Atlassian and Cloudera Data Platform
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 | Cloudera Data Platform objects | How this pairing syncs | |
|---|---|---|---|
| Issue Comments Threaded discussion synced into linked tickets in external systems. | Views SQL views that can present curated, sync-ready projections of raw lake data. | Issue Comments is specific to Atlassian and Views to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Attachments Files on issues mirrored to paired records where needed. | Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | Attachments is specific to Atlassian and Partitions to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Custom Fields Instance-specific fields (customfield IDs) that carry most business-specific data in syncs. | Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. | Custom Fields is specific to Atlassian and Object store / HDFS files to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Workflows and Statuses Status transitions mapped to stages in the paired system. | Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Workflows and Statuses is specific to Atlassian and Databases to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Users and Groups Assignees and reporters matched to identities in other tools. | Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | Users and Groups is specific to Atlassian and Hive tables to Cloudera Data Platform — each maps to any object or custom field on the other side. | |
| Confluence Pages Documentation content readable and writable through the Confluence REST API. | Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Confluence Pages is specific to Atlassian and Impala tables to Cloudera Data Platform — each maps to any object or custom field on the other side. |
How changes propagate between Atlassian and Cloudera Data Platform
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 Cloudera Data Platform 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 Cloudera Data Platform as a row-level write, with types converted between the two schemas.
Cloudera Data Platform Atlassian Interval-based propagation
DetectionStacksync polls Cloudera Data Platform for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL on timestamp or partition columns.
DeliveryEach detected change is written to Atlassian through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Cloudera Data Platform: Constrained by cluster capacity and admission control rather than API rate limits.
What ships with Atlassian ⇄ Cloudera Data Platform
Connect Atlassian and Cloudera Data Platform for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Atlassian–Cloudera Data Platform connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Atlassian or Cloudera Data Platform 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 Cloudera Data Platform record.
Observability
Monitoring
Track your Atlassian ⇄ Cloudera Data Platform 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 Cloudera Data Platform.
How the Atlassian and Cloudera Data Platform 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
Cloudera Data Platform
- Integration surface
- JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs
- Authentication
- Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway
- Change detection
- Polling via SQL on timestamp or partition columns; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Constrained by cluster capacity and admission control rather than API rate limits
How it works
How to connect Atlassian to Cloudera Data Platform — 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 Cloudera Data Platform 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
Cloudera Data Platform
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Atlassian and Cloudera Data Platform 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 ⇄ Cloudera Data PlatformCustomers 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 Cloudera Data PlatformCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Atlassian and Cloudera Data Platform integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Atlassian and Cloudera Data Platform: authenticate both systems, choose the objects to sync (such as Atlassian's Issue Comments and Attachments), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Atlassian side: Boards and Sprints, Issue Comments, Attachments, Custom Fields, plus custom fields where Atlassian exposes them. On the Cloudera Data Platform side: Object store / HDFS files, Databases, Hive tables, Impala 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 Cloudera Data Platform: History that outlives the tool; Analytics on Atlassian's data; Cross-tool reporting. A continuously synced copy in Cloudera Data Platform preserves a queryable record even as data ages out of Atlassian or gets changed inside it.
-
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. Cloudera Data Platform: JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs. Authentication: Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway. Stacksync manages authentication, retries, and rate limits on both sides.
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Atlassian: Each Atlassian product has its own REST API and resource model; a sync spanning Jira and Confluence talks to separate endpoints under one Atlassian identity. Cloudera Data Platform: Access is commonly brokered by Apache Knox and secured with Kerberos or LDAP, which integration tooling must support. Stacksync's field mapping accounts for these differences between Atlassian and Cloudera Data Platform without custom code.
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 374 integrations available for Atlassian and Cloudera Data Platform.
Popular · 7 of 374
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Atlassian ⇄ Vertica -
Atlassian ⇄ Yellowbrick -
Atlassian ⇄ Snowflake -
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Cloudera Data Platform ⇄ Adobe Sign -
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Cloudera Data Platform ⇄ Docusign
No integrations match .
