No-code pipeline · Jira → SQL Server

Send data from Jira to SQL Server

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From Jira to SQL Server: managed, scheduled, no code.

Kondado connects Jira to SQL Server, replicating your agile project data on a configurable schedule ranging from every 5 minutes to daily, making 13 pipelines with 165 fields available in your database for analysis and reporting.

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Send Jira Data to SQL Server

Sending Jira data to SQL Server requires selecting the specific pipelines you need from your agile project management environment and configuring the replication schedule that fits your reporting needs. With Kondado, you establish a direct connection to your Jira instance, choose from 13 available pipelines covering issues, sprints, boards, and project metadata, and set automated updates to run every 5 minutes, hourly, or daily.

Once your data arrives in SQL Server, you can build custom reports analyzing sprint velocity, track issue resolution times across projects, and join Jira metrics with CRM or financial data stored in your database. This enables comprehensive project performance dashboards and automated reporting workflows that keep stakeholders informed without manual data exports.

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The Issues pipeline delivers comprehensive ticket data including status, assignees, and due dates directly into your SQL Server tables, enabling you to calculate resolution times and backlog trends using T-SQL queries. Combined with the Issues Change History pipeline, you can track field modifications over time to analyze how story points or priorities evolve throughout your sprints. The Boards pipeline brings Kanban and Scrum board configurations into SQL Server, allowing you to correlate column transitions with actual completion rates.

By querying this replicated data alongside sales figures from your CRM or budget data from ERP systems, you create unified project cost analysis and resource allocation reports. Teams can build custom dashboards in Power BI or Looker Studio connected directly to SQL Server, visualizing agile metrics alongside business KPIs for complete project visibility.

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Replicated to SQL Server

Jira data available for SQL Server

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

available pipelines

165

extractable fields

SQL Server

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 SQL Server →

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How to send Jira data to SQL Server

Sync data automatically — no code, no manual exports.

Connect Your Jira Account

Authenticate your Jira instance in Kondado by providing your site URL and API credentials, granting access to your projects, boards, and issue data.

Configure SQL Server Destination

Enter your SQL Server connection details including server address, database name, and authentication credentials to establish the target location for your replicated Jira pipelines.

Select Pipelines and Schedule

Choose from the 13 available Jira pipelines such as Issues, Boards, and Sprints, then set your preferred update frequency from 5 minutes to daily to automate data replication.

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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 SQL Server automatically

How do I replicate Jira Issues with custom fields to SQL Server? ▼

Select the Issues pipeline to capture standard ticket data, then add the Issues Custom Fields pipeline to include your specific Jira configurations. Both pipelines write to dedicated tables in SQL Server, allowing you to join custom field values with issue metadata using standard SQL queries.

What is the minimum sync frequency for Jira data in SQL Server? ▼

Kondado supports automated updates as frequent as every 5 minutes, with options for 15-minute intervals, hourly, or daily schedules based on your reporting requirements. You configure the specific cadence during pipeline setup, ensuring your SQL Server database reflects recent project changes without overwhelming your Jira API limits.

Can I combine Jira sprint data with CRM data in SQL Server? ▼

Yes, once both data sources write to SQL Server, you can write queries joining the Boards Sprints pipeline with CRM tables to analyze how development velocity correlates with sales cycles. This unified approach enables comprehensive reports showing the relationship between feature releases and customer acquisition metrics.

How does Kondado handle Jira Issues Change History in SQL Server? ▼

The Issues Change History pipeline creates records of every field modification, including the changelog ID, change date, and author, allowing you to reconstruct issue lifecycles. This historical data enables trend analysis showing how estimates evolve and helps identify bottlenecks in your approval workflows.

Can I visualize Jira data from SQL Server in Power BI? ▼

Absolutely, after replicating your Jira data to SQL Server, connect Power BI directly to your database to build custom agile dashboards. You can also send data to Google Sheets or BigQuery if your organization prefers those visualization platforms.

How do I track board configuration changes using the Boards Column Configuration pipeline? ▼

This pipeline replicates column names, board IDs, and status URLs to SQL Server, allowing you to monitor how your Kanban or Scrum board structures change over time. By comparing these configurations against the Boards Issues Relationship data, you can analyze whether workflow modifications improve cycle times and team throughput.

What happens when I add new custom fields to Jira after initial setup? ▼

Kondado automatically detects new fields in your Issues Custom Fields pipeline during subsequent sync cycles, adding them as new columns in your SQL Server tables. This ensures your analytics stay current with evolving project management requirements without manual schema adjustments.

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Related on Kondado

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