Send data from Jira to Redshift

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Replicate Jira Data to Redshift Automatically

Sending Jira data to Redshift requires a reliable data source that can extract project management information and load it into your AWS data warehouse without manual exports. Kondado provides a direct integration between Jira and Redshift, allowing you to replicate boards, issues, sprints, and project metadata on a configurable schedule. The platform handles the data extraction and transformation, ensuring your Redshift cluster contains structured Jira data ready for complex SQL queries and business intelligence analysis.

Kondado replicates 13 Jira pipelines including Issues, Boards, Sprints, and Projects to Amazon Redshift on a configurable schedule ranging from every 5 minutes to daily, enabling automated data warehousing of agile project management data without coding.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Once your Jira data lands in Redshift, you can analyze the Issues pipeline to track ticket resolution times and identify bottlenecks in your development workflow using standard SQL. The Boards and Sprints pipelines enable you to correlate board configurations with sprint velocity and completion rates, helping teams optimize their agile ceremonies and resource allocation. By combining these datasets in Redshift with information from other business systems, you create comprehensive project health dashboards that connect granular task-level details with strategic timelines and cross-functional dependencies.

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Jira data available for Redshift

13
available pipelines
165
extractable fields

Available integrations

Integration Description
Boards Includes fields such as id, name, and type of the board, along with the associated project ID.
Boards Column Configuration Presents fields such as column name, board ID, and status URL, allowing insight into the board's structure.
Boards Issues Relationship Shows the relationship between issues and boards with fields such as issue ID and issue key.
Boards Sprints Includes information about sprints, such as sprint ID, start date, and sprint state.
Issues Contains fields such as issue ID, key, due date, and current status, enabling task management.
Issues Custom Fields Allows the inclusion of custom fields for issues, facilitating the customization of information.
Issues Change History Records changes with fields such as changelog ID, change date, and change author.
Issues Web Links Includes links related to issues, allowing quick access to external resources.
Issues Activity Logs Provides activity logs with fields such as issue ID and activity date, useful for auditing.
Issues Links Presents links between issues, allowing visualization of relationships and dependencies between tasks.
Projects Includes fields such as id, project name, and project type, enabling effective viewing and management of ongoing projects.
Sprints: relationship with issues Presents fields such as sprint id, board id, and sprint state, facilitating the tracking of progress for related tasks.
Status Contains information on id, status name, and description, allowing understanding of the current state of tasks and their lifecycle.
Boards
Includes fields such as id, name, and type of the board, along with the associated project ID.
Boards Column Configuration
Presents fields such as column name, board ID, and status URL, allowing insight into the board's structure.
Boards Issues Relationship
Shows the relationship between issues and boards with fields such as issue ID and issue key.
Boards Sprints
Includes information about sprints, such as sprint ID, start date, and sprint state.
Issues
Contains fields such as issue ID, key, due date, and current status, enabling task management.
Issues Custom Fields
Allows the inclusion of custom fields for issues, facilitating the customization of information.
Issues Change History
Records changes with fields such as changelog ID, change date, and change author.
Issues Web Links
Includes links related to issues, allowing quick access to external resources.
Issues Activity Logs
Provides activity logs with fields such as issue ID and activity date, useful for auditing.
Issues Links
Presents links between issues, allowing visualization of relationships and dependencies between tasks.
Projects
Includes fields such as id, project name, and project type, enabling effective viewing and management of ongoing projects.
Sprints: relationship with issues
Presents fields such as sprint id, board id, and sprint state, facilitating the tracking of progress for related tasks.
Status
Contains information on id, status name, and description, allowing understanding of the current state of tasks and their lifecycle.

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How to send Jira data to Redshift

Sync data automatically — no code, no manual exports.

1
Connect Your Jira Account

Authenticate your Jira data source by providing your instance URL and API credentials in Kondado's interface. The platform validates your connection and retrieves available project metadata automatically.

2
Configure Redshift Destination

Enter your Amazon Redshift cluster credentials including host, database name, and user permissions to establish the destination connection. Kondado tests the connection to ensure write access for creating tables and loading data.

3
Select Pipelines and Schedule

Choose from 13 available pipelines such as Issues, Boards, and Sprints, then set your preferred update frequency ranging from 5 minutes to daily. Kondado begins replicating data immediately based on your configuration, keeping your warehouse synchronized automatically.

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Frequently Asked Questions (FAQ)

Answers about sending Jira data to Redshift automatically

How does Kondado replicate Jira data to Redshift without coding?
Kondado provides a no-code data source that connects directly to your Jira instance using your credentials. The platform automatically extracts data from your selected pipelines and loads it into your Redshift cluster, handling schema creation and data type mapping. You configure the connection once, and Kondado manages the ongoing data replication on your chosen schedule.
What Jira project information is available in the Issues pipeline?
The Issues pipeline contains core ticket data including issue ID, key, due date, current status, and assignee information. You also get access to the Issues Custom Fields pipeline, which captures your specific Jira configurations and custom metadata, allowing you to analyze bespoke workflows and categorizations unique to your organization.
How often can I update Jira data in my Redshift warehouse?
Kondado offers flexible scheduling options ranging from every 5 minutes to daily intervals, allowing you to balance data freshness with warehouse compute costs. You can configure different update frequencies for individual pipelines, ensuring high-priority Issues data updates frequently while historical data refreshes less often.
Can I combine Jira data with other sources in Redshift?
Yes, Redshift serves as a central repository where Jira data can coexist with information from sales, marketing, and finance tools. You can join Jira Issues with CRM data or marketing metrics that you also replicate to Redshift, then send consolidated datasets to Power BI or Looker Studio for comprehensive visualization.
What format does Jira data take when stored in Redshift?
Kondado creates structured relational tables in Redshift for each pipeline, with standard PostgreSQL data types that preserve Jira's native field structures. Issues, Boards, and Sprints data arrives as normalized tables that you can query directly using SQL, join with existing warehouse tables, or connect to business intelligence tools for further analysis.
Does Kondado support Jira custom fields in Redshift?
Yes, the Issues Custom Fields pipeline specifically captures your bespoke Jira configurations and custom field values. This data arrives in Redshift as structured columns alongside standard fields, allowing you to analyze personalized workflows, custom categorizations, and organization-specific metadata that standard Jira exports often miss.
How do I track historical changes to Jira tickets in Redshift?
The Issues Change History pipeline captures every modification made to your tickets, including changelog ID, change date, and change author. This creates a complete audit trail in Redshift that enables trend analysis, compliance reporting, and velocity tracking by showing exactly when statuses changed and who made those updates.

Try out all the features for free for 14 days