Stream data from Jira to Dekaf
Move data from Jira to Dekaf in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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- 30-day free trial


- 200+Of connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate Jira with Dekaf in 3 simple steps
Connect Jira as your data source
Set up a source connector for Jira in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
Configure Dekaf as your destination connector
Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to Dekaf.
Deploy and Monitor Your End-to-End Data Pipeline
Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

Jira connector details
The Jira source connector captures data from Jira Platform, Jira Software, and Jira Service Management REST APIs into Estuary collections. It can replicate Jira issues, comments, changelogs, projects, boards, sprints, users, workflows, and other Jira resources so product, engineering, support, and analytics teams can centralize Jira data for reporting and operational analysis.
- Capture Jira data from Jira Platform, Jira Software, and Jira Service Management APIs into Estuary collections.
- Replicate key Jira resources such as issues, issue comments, changelogs, projects, boards, sprints, users, workflows, statuses, and service desks.
- Map each selected Jira resource to a separate Estuary collection through its own binding.
- Connect using your Jira domain, account email, and Jira API token.
- Set a UTC start date to control how far back Estuary should replicate Jira data; if left blank, the connector defaults to 30 days before the present.
- Optionally limit issue replication to specific Jira project IDs, or leave the project filter blank to replicate issues from all projects.

Dekaf connector details
- Merge-based materializations to sync only what's changed
- Low-latency delivery from streaming and batch sources
- Automatic schema alignment so your destination matches your pipeline's evolving data
- Flexible deployment models, including BYOC and hybrid for enterprise governance
- Unified streaming + batch outputs in a single tool
- End-to-end security and compliance for sensitive data workloads
Estuary in action
See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.
Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

Jira to Dekaf pricing estimate
Estimated monthly cost to move 800 GB from Jira to Dekaf is approximately $1,000.
Data moved
Choose how much data you want to move from Jira to Dekaf each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.



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Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this Jira to Dekaf integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
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DataOps made simple
Add advanced capabilities like schema inference and evolution with a few clicks. Or automate your data pipeline and integrate into your existing DataOps using Estuary's rich CLI.





































