Jira
Engineering Analytics
Sync Jira data anywhere.
- Certified
- Generally available
- 55 streams
- 9 entities
- Read & write
- 55Streams
- 9Entities
- 7Actions
- 50+Destinations
Everything Jira can do in Airbyte
Sync to your warehouse
Land 55 Jira tables in 50+ destinations on a schedule you control.
Live entity actions
Read, create, update and delete Jira records at runtime through typed entity actions.
Context store search
Query synced Jira data with filters, sorting and semantic search, without spending Jira API rate limits.
Incremental syncs
Pull only the records that changed since the last run instead of reloading everything.
Sync capabilities
- Full Refresh SyncSupported
- Incremental SyncSupported
- Available onCloud, Self-Managed Enterprise
- Destinations50+ Airbyte connectors
- Connector version6.0.1
Set up in 10 steps
- First, navigate to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
- Click on the "Add Source" button in the top right corner of the screen.
- Select "Jira" from the list of available sources.
- Enter a name for your Jira source connector and click "Next".
- Enter your Jira credentials, including the Jira URL, email address, and API token.
- Test the connection to ensure that the credentials are correct and the connection is successful.
- Select the Jira projects and issue types that you want to replicate in Airbyte.
- Choose the replication frequency and any other settings that you want to apply to your Jira source connector.
- Click "Create Source" to save your Jira source connector and begin replicating data from Jira to Airbyte.
- It is important to note that the specific steps for connecting your Jira source connector may vary depending on your specific use case and the version of Jira that you are using. For more detailed instructions and troubleshooting tips, refer to the Airbyte documentation or consult with a Jira expert.
Every table you can sync from Jira
Application roles
Avatars
Boards
Dashboards
Filters
Filter sharing
Groups
Issue fields
Issue custom field contexts
Issue custom field options
Issue link types
Issue navigator settings
Supported Jira actions
API Search
Create
Write a new record back into Jira.
Get
Fetch a single record by ID.
Update
Patch fields on an existing record.
Delete
Remove a record.
Context Store Search
Query synced data with filters and sorting, with no API rate limits.
List
Read live records straight from the Jira API.
Authenticate Jira once
API Token
Service Account
OAuth2.0
Recommended
What teams build with Jira
Show me all open issues in my Jira instance
List recent issues created in the last 7 days
List all projects in my Jira instance
Show me details for the most recently updated issue
List all users in my Jira instance
Show me comments on the most recent issue
Related connectors
Common questions
Do I need more than one Jira connection?
No. One Jira authorization powers both the scheduled syncs that land data in your destination and the entity actions your agents call at runtime.
Do Jira entity actions need a sync to run first?
No. Entity actions read and write through the Jira API as they are called, so they work immediately. Context store search is the exception: it queries data Airbyte has already synced, which is what lets it filter and sort without spending API rate limits.
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
What data can you extract from Jira?
Jira's API provides access to a wide range of data related to project management and issue tracking. The following are the categories of data that can be accessed through Jira's API:
1. Issues: This includes all the information related to the issues such as issue type, status, priority, description, comments, attachments, and more.
2. Projects: This includes information about the projects such as project name, description, project lead, and more.
3. Users: This includes information about the users such as user name, email address, and more.
4. Workflows: This includes information about the workflows such as workflow name, workflow steps, and more.
5. Custom fields: This includes information about the custom fields such as custom field name, type, and more.
6. Dashboards: This includes information about the dashboards such as dashboard name, description, and more.
7. Reports: This includes information about the reports such as report name, description, and more.
8. Agile boards: This includes information about the agile boards such as board name, board type, and more.
Overall, Jira's API provides access to a vast amount of data that can be used to improve project management and issue tracking.
How do I transfer data from Jira?
1. First, navigate to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
2. Click on the "Add Source" button in the top right corner of the screen.
3. Select "Jira" from the list of available sources.
4. Enter a name for your Jira source connector and click "Next".
5. Enter your Jira credentials, including the Jira URL, email address, and API token.
6. Test the connection to ensure that the credentials are correct and the connection is successful.
7. Select the Jira projects and issue types that you want to replicate in Airbyte.
8. Choose the replication frequency and any other settings that you want to apply to your Jira source connector.
9. Click "Create Source" to save your Jira source connector and begin replicating data from Jira to Airbyte.
It is important to note that the specific steps for connecting your Jira source connector may vary depending on your specific use case and the version of Jira that you are using. For more detailed instructions and troubleshooting tips, refer to the Airbyte documentation or consult with a Jira expert.
What are top ETL tools to transfer data from Jira?
The most prominent ETL tools to transfer data to include: Airbyte, Fivetran, StitchData, Matillion, Talend Data Integration. These tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into and other databases, data warehouses and data lakes, enhancing data management capabilities.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
Start moving Jira data today
Free for 14 days on Airbyte Cloud. One connection powers your scheduled syncs and your live Jira actions.