No-code pipeline · Jira → Redshift

Send data from Jira to Redshift

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From Jira to Redshift: managed, scheduled, no code.

Creating a pipeline that sends data from Jira to Redshift data warehouses takes only a few minutes with Kondado. And the whole integration from Jira to Redshift is managed and executed by our platform. With Kondado, you can focus on extracting value from Jira data and combining it with other data in your Redshift data warehouse

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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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Replicated to Redshift

Jira data available for Redshift

Tables Kondado writes into your Redshift, on a schedule you control.

available pipelines

165

extractable fields

Redshift

Destination

Available integrations

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.

See all available data → Send Jira to Redshift →

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How to send Jira data to Redshift

Sync data automatically — no code, no manual exports.

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.

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.

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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Send data from Jira to other destinations

Jira > Looker Studio

Jira > Power BI

Other visualizations

Jira > Amazon S3

Jira > BigQuery

Jira > Excel

Jira > Google Sheets

Jira > MySQL

Jira > PostgreSQL

Jira > Redshift

Jira > SQL Server

Choose a tool to visualize your Jira data

If the software you need is not listed, drop us a messagem. You can use almost every tool

Jira > Airtable

Jira > Alteryx

Jira > Amazon Quicksight

Jira > BIMachine

Jira > Cortex

Jira > Data Studio

Jira > Geckoboard

Jira > Grafana

Jira > IBM Cognos Analytics

Jira > Klipfolio

Jira > Looker Studio

Jira > Looker

Jira > Looqbox

Jira > Metabase

Jira > Microstrategy

Jira > Pentaho

Jira > Power BI

Jira > Qlik Cloud Analytics

Jira > Qlik Sense

Jira > Qlik

Jira > QlikView

Jira > Redash

Jira > Superset

Jira > Tableau

Jira > BI TOTVS

Jira > Zoho Analytics

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

Related on Kondado

Try out all the features for free for 14 days