What is the difference between Atlassian Data Center and Server?
Atlassian Data Center and Server are two distinct self-hosted deployment models for Atlassian products (Jira, Confluence, Bitbucket, and others), each designed for different organizational needs and scales. The fundamental technical difference is that Data Center supports a multi-node cluster architecture while Server operates on a single application server.
While both offer the same core functionality, Data Center is purpose-built for enterprises requiring high availability, performance at scale, and operational flexibility, whereas Server is suited for smaller organizations with more modest deployment requirements.
An important strategic consideration is that Atlassian announced the end-of-life for both Server and Data Center products. Server already reached end-of-life in February 2024, while Data Center is scheduled for end-of-life on March 28, 2029, with new sales ceasing on March 30, 2026. This reflects Atlassian's cloud-first strategy. Organizations still on Server or considering Data Center should evaluate whether a migration to Atlassian Cloud aligns with their long-term roadmap, particularly given the remaining runway.
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How does Jira Data Center performance compare to cloud alternatives?
Jira Data Center performance is robust and suitable for enterprises requiring high scalability and customisation, whereas cloud alternatives offer more flexible management but may have limits on customisation.
Disclaimer: Jira Data Center will end in 2029 and is no longer available for new clients. Read more about Jira Server EOL.
How to migrate Jira from one server to another?
To migrate Jira from one server to another, the key steps involve preparation, backup, installation, data migration, and testing:
- Perform pre-migration checks: Verify your Jira license is valid, check compatibility of the new server’s OS, database, and hardware with Jira, and confirm the same time zones are configured to avoid date/time issues. Verify compatibility of any third-party apps used in Jira.
- Back up data: Stop the existing Jira instance on the old server and back up your Jira Home directory (which contains attachments and configuration) and your Jira database. These backups are crucial for restoring your data on the new server.
- Install Jira on the new server: Download and install a fresh Jira instance on the new server, in a different directory than the old installation.
- Restore data on new server: Copy the backup of the Jira Home directory to the new server and configure the Jira application properties file to point to this directory. If migrating to a new database or database server, update the database configuration file with the new connection parameters. Reapply any modifications related to user management tools like Crowd.
- Install database driver: If required for your database type (e.g., Oracle, MySQL), install the appropriate JDBC driver on the new server.
- Start Jira on the new server: Start the Jira application and verify that all data and customizations are intact and functioning as expected.
- Testing: Validate the migrated Jira environment by checking project data, workflows, users, and permissions. Conduct thorough testing before switching production traffic to the new server.
It is highly recommended to first do the migration in a test environment before performing it in production. If any issues arise during production migration, you should continue using the old server until resolved.
For Jira Server to Cloud migrations, Atlassian provides the Jira Cloud Migration Assistant tool, which guides through a different process focusing on cloud readiness and user data migration.
How to migrate Jira database?
Migrating from Jira to another platform can be a complex process, and it typically involves several key steps:
- Assessment and planning: Before starting the migration, it's crucial to assess the current Jira setup, including the number of projects, custom fields, workflows, and any integrations or add-ons in use. This helps in planning the migration strategy and identifying potential challenges.
- Data export: The next step is to export data from Jira. This can be done using Jira's built-in export tools, such as exporting issues to a CSV file. The export should include all necessary data like issues, attachments, and user information.
- Data mapping and transformation: Once the data is exported, it needs to be mapped to the new platform's data structure. This may involve transforming the data to fit the new system's requirements, such as converting custom fields or workflows to the new format.
- Migration tools: Depending on the target platform, there may be specific migration tools available to facilitate the process. For example, if migrating to a cloud-based system, there might be cloud migration assistants or third-party tools that can help automate parts of the migration.
- Testing: Before performing the final migration, it's important to test the process in a staging environment. This helps identify any issues that might arise during the actual migration and allows for adjustments to be made.
- Execution: After successful testing, the migration can be executed. This involves importing the transformed data into the new platform and ensuring that all data is correctly mapped and accessible.
- Validation and cleanup: Post-migration, it's essential to validate that all data has been migrated correctly and that the new system is functioning as expected. This includes checking for any missing data, broken links, or issues with workflows. Any necessary cleanup should be performed at this stage.
- Training and support: Finally, provide training and support to users to help them transition to the new platform. This ensures that they are comfortable with the new system and can use it effectively.
Each migration is unique, and the specific steps may vary depending on the complexity of the Jira setup and the target platform. It's often recommended to work with experienced professionals or solution partners to ensure a smooth migration process.
