How to Export Data from Jira to SQL Database: Complete Step-by-Step Instruction

Jira is the epitome of a project management solution. It is cloud-based and provides a single centralized source of truth for teams to carry out project-based tasks. Under the hood, it offers Jira reporting but may be limited to specific use cases.

As a result, many teams find the need to export data from Jira to SQL databases to enhance their reporting and Jira data management capabilities. It is where Jira SQL database integration with SQL Connector for Jira comes into play, offering an enterprise-grade app that automates the transfer of Jira data to SQL databases of your choice for improved Jira data management and reporting.

This article will explore an easier way to integrate Jira with your SQL database with Alpha Serve's SQL Connector for Jira. We will cover how this integration can streamline Jira data export to popular SQL databases and provide you with simple steps to set up the connector. Let's get started!

As organizations navigate the complexities of project management, many have turned to solutions like Jira to manage and streamline their operations. Jira, a versatile project management tool, is a rich source of valuable data. It enables teams to track tasks, manage workflows, and collaborate efficiently. Although Jira provides many advanced features, its native reporting may not fulfill all needs, especially as businesses scale and data complexities increase. This is when SQL databases become helpful.

Why Jira need SQL? SQL, or Structured Query Language, is a standard language for managing and manipulating relational databases. A SQL database is a type of database that utilizes SQL to access, update, and manipulate data. Among the most popular SQL databases include PostgreSQL, Microsoft SQL Server, MySQL, MariaDB, and more. These databases are renowned for their ability to handle complex queries and vast data sets, providing powerful tools for data analysis.

Connecting Jira to an SQL database offers many benefits, effectively enhancing an organization's ability to leverage its Jira data. Here are some reasons why integrate Jira with SQL database:

Jira's default reporting capabilities, while robust, might not always meet all specific reporting needs. SQL databases, on the other hand, support complex querying, enabling teams to create sophisticated, in-depth Jira reports. Such reports can yield deeper insights into company performance and uncover hidden trends, driving data-informed decision-making.

Modern businesses often use a bunch of tools in tandem with Jira. Consolidating all this data into a single SQL database allows for more extensive and powerful analysis. Teams can examine Jira data alongside data from other systems and tools to unveil correlations and patterns that would otherwise remain hidden.

Preserving a long-term backup or archive of Jira data in a SQL database ensures that valuable historical Jira data remains accessible, even if the company chooses to stop using Jira in the future. It's a practical strategy for long-term data retention and preservation.

SQL databases open up avenues for advanced Jira data analytics. Data scientists can use Jira data stored in the database to build machine learning models and perform predictive analysis, opening up a range of possibilities for future project planning and risk assessment.

If a company uses custom software that also uses a SQL database, integrating Jira data into this database can greatly simplify data management and workflow automation. It also enables tighter synchronisation between different systems.

Having explored the various reasons for integrating Jira and SQL databases, we now focus on the practical use cases highlighting the immense potential of integrating Jira and your SQL database. Organizations can unlock many possibilities for Jira data analysis, reporting, and workflow optimization by connecting Jira with a SQL database. While the reasons for integration provide a foundation for understanding the value of this integration, the use cases demonstrate how businesses across different industries can effectively harness the power of Jira and SQL databases in real-world scenarios. Let's explore some universal use cases to discover how organizations leverage their data in SQL databases:

SQL Connector for Jira is a user-friendly enterprise-ready app that lets you connect Jira data to SQL databases. With it, you can export data from Jira to your preferred SQL database in minutes.

Here, you can choose between different SQL databases. Please note that the availability of these databases may depend on your Jira hosting option. Currently, it supports the following:

• Microsoft SQL Server
• PostgreSQL
• MySQL
• Oracle
• MariaDB
• H2

With it, you can directly export structured Jira data into the database. From there, you can use the latest data to gain deep insights, which results in better overall decision-making.

SQL Jira Integration provides advanced capabilities for SQL experts to fine-tune data further using complex queries with adjustable parameters. It allows for efficient data sorting, analysis, and filtering, enabling teams to extract valuable insights and information from Jira data.

The SQL Connector for Jira also offers customized data export options, allowing teams to apply SQL or basic filters for exporting Jira data according to their specific requirements. This customization capability will enable teams to tailor the exported data to their specific needs, ensuring that the data extracted from Jira is relevant and valuable for their reporting, analysis, and decision-making processes.

Apart from the above, the other key SQL Connector features include:

• Scheduled data refresh: Get the latest data by automating it through scheduled refresh or Cron.
• No-code integration: You need no technical or coding skills to use the SQL Connector. Once set up, it offers seamless data export.
• Direct SQL Jira Connection: The enterprise-grade connector directly connects Jira and SQL databases without needing a third-party solution. All you need to do is use the necessary credentials.
• Secure data: You're in complete control over your data. You can set up data access permission across the board.
• Automated data schema: The Jira SQL plugin can automate data schema by correctly connecting the table's relationships.

Before starting to configure SQL Jira integration, you must install the connector. Mention you must have Administrator permissions in Jira. Select the "Manage apps" section under the Jira Administration menu. You'll be directed to the page for managing apps. Use the search bar in the "Find new apps" section to find "SQL Connector for Jira Alpha Serve". Look through the search results for the application. Click "Free Trial" to obtain a 30-day free trial license. Click "Buy now" to check out the application right now. On your Jira instance, the application will be installed immediately.

As an alternative, you can get SQL Connector for Jira straight from the Atlassian Marketplace by going to the product page.

To set up SQL Jira Integration with SQL Connector for Jira, follow the steps mentioned below.

2. Click on the Security tab and select Create and manage API tokens.

3. Click the Create API token button to generate a new token.

4. Enter a name for the API token and click Create.

5. Once the API token is created, copy it, as you won't be able to see it again.

6. Now, Go to Apps and then choose SQL Connector for Jira.

7. Go to Tokens > Jira API token, and enter the token. Finally, click on Validate and Save.

1. In the Title section of SQL Connector for Jira, enter the name and description for your data source. You can also edit the share settings to specify who can access the data source.

2. Click the Share settings button to select the relevant groups and users. Once done, click on Save to apply changes.

3. In the next step, you can choose the filter issue type for your data source. You have three options to choose from:

• "All": This option allows you to export all existing issues from Jira.
• "Select by JQL": This option enables you to create custom requests and filter data based on JQL (Jira Query Language) queries.
• "Basic": This option lets you filter the data using standard field filters for Projects, Issue Types, and Statuses.

4. In the Fields section, you can select the field names that you want to include in your data source. You can search for a field name using the Search Field option or the Magnifier icon to browse and add fields. It allows you to fine-tune the data that will be exported to your SQL database.

5. Before closing the data source creation page, you can also preview the data source in different formats, such as raw or ERD (Entity Relationship Diagram), to ensure that the data is filtered and mapped correctly.

6. Once configured the data source according to your requirements, click on the Save button to save the data source settings.

The last step includes exporting data. To do so, follow the steps mentioned below.

1. Open SQL Connector for Jira and search for the data source you want to export. Once done, click on the Export data button.

2. Next, you can set up a new connection(for first-time users) or choose existing connections. Here, enter all the necessary features and click on Save.

3. Lastly, click on the Export data button again. It’ll set up the connection, and the button status will change to Cancel export.

That’s it! If you need more help related to installation on How to set up SQL Connector for Jira Data Center, check out its documentation page.

SQL Jira integration can save you plenty of headaches. Once done, you can enjoy uninterrupted fresh data, ready for Jira data analysis. However, you must use SQL Jira Cloud Connector for the best results. It removes the need to know coding or technical skills. Moreover, it automates the Jira export process and helps improve data consistency and related performance.