Do I need an account with Jira?

Yes. You connect your own Jira account once, from Ingest, and the data comes from what that account can see.

How fresh is the data?

As fresh as your schedule: daily by default, or weekly or monthly. Schedules as often as every 15 minutes are on the Enterprise plan.

Will running it again create duplicate rows?

No. Each row is stored once, by its key: when a run reads a row that is already there, it replaces that copy instead of adding a second one.

Do I need to write code?

No. Ingest builds, runs and maintains the connector. Someone with access to your warehouse connects it once, following a short guide.

Jira

Productivity

Ready to use

Jira data, published as Jira publishes it. Ingest delivers this data to a data warehouse you own as 10 tables, and updates it on the schedule you choose. There is no code to write and nothing to install.

What you get

Table	Each row is
boards `boards`	Every agile board (scrum, kanban and team-managed) with the project it belongs to.
fields `fields`	Every issue field, system and custom, with its name and type; custom field ids here name the customfield_ columns in `issues`.
issue_changelogs `issue_changelogs`	Each issue's change history, one row per change set with its author and time; the child table of items lists every field that changed, from and to. `_ingest_parent_key` is the issue id.
issue_types `issue_types`	Every issue type (task, bug, story, epic, subtask and custom types) and the scope it belongs to.
issues `issues`	One row per issue with every field the account can see, standard and custom, as columns; changed issues are read again each run. Arrays such as components, fix versions, links, subtasks and attachments land as child tables; the rich-text description and the embedded first page of comments and worklogs land as JSON.
priorities `priorities`	Every issue priority, in the site's order.
projects `projects`	Every project the account can see, with its lead, category, issue types and insight counts.
resolutions `resolutions`	Every issue resolution (done, won't do, duplicate and the site's own).
statuses `statuses`	Every workflow status with its status category (to do, in progress, done).
users `users`	Every Atlassian account the site knows, active, inactive and deleted, including app accounts; email addresses appear only where the user's profile shows them.

How it works

Choose Jira. Connect your Jira account once, from Ingest.
Pick where it goes. BigQuery, Snowflake, Databricks, Redshift and 10 more, in an account you own.
Pick a schedule. Daily is the default, and weekly and monthly are there too.
Ingest runs it from then on. If a run fails, your dashboard shows which table and why.

Questions

Do I need an account with Jira?: Yes. You connect your own Jira account once, from Ingest, and the data comes from what that account can see.
Which warehouses can Jira data go to?: Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL and Snowflake, in an account you own.
How fresh is the data?: As fresh as your schedule: daily by default, or weekly or monthly. Schedules as often as every 15 minutes are on the Enterprise plan.
Will running it again create duplicate rows?: No. Each row is stored once, by its key: when a run reads a row that is already there, it replaces that copy instead of adding a second one.
Do I need to write code?: No. Ingest builds, runs and maintains the connector. Someone with access to your warehouse connects it once, following a short guide.

For your data team: technical reference

Connector jira, version 0.1.0, a REST source, status beta, authentication basic.

Vendor documentation: https://developer.atlassian.com/cloud/jira/platform/rest/v3/

Configuration

Key	Label	Type	Required
`site`	Your atlassian.net site	string	yes

Resources

Resource	Status	Plan	Write	Primary key	Overrides
`boards` Every agile board (scrum, kanban and team-managed) with the project it belongs to.	beta	full	merge	`id`	-
`fields` Every issue field, system and custom, with its name and type; custom field ids here name the customfield_ columns in `issues`.	beta	full	merge	`id`	-
`issue_changelogs` Each issue's change history, one row per change set with its author and time; the child table of items lists every field that changed, from and to. `_ingest_parent_key` is the issue id.	beta	parent_child	merge	`id`	-
`issue_types` Every issue type (task, bug, story, epic, subtask and custom types) and the scope it belongs to.	beta	full	merge	`id`	-
`issues` One row per issue with every field the account can see, standard and custom, as columns; changed issues are read again each run. Arrays such as components, fix versions, links, subtasks and attachments land as child tables; the rich-text description and the embedded first page of comments and worklogs land as JSON.	beta	watermark	merge	`id`	backfill_days
`priorities` Every issue priority, in the site's order.	beta	full	merge	`id`	-
`projects` Every project the account can see, with its lead, category, issue types and insight counts.	beta	full	merge	`id`	-
`resolutions` Every issue resolution (done, won't do, duplicate and the site's own).	beta	full	merge	`id`	-
`statuses` Every workflow status with its status category (to do, in progress, done).	beta	full	merge	`id`	-
`users` Every Atlassian account the site knows, active, inactive and deleted, including app accounts; email addresses appear only where the user's profile shows them.	beta	full	merge	`accountId`	-

Setting up the destination is its own short guide, one per warehouse or lake: Amazon S3, Google Cloud Storage, Azure Blob Storage, Apache Iceberg, Ingest Managed Lakehouse, MotherDuck, Postgres, Amazon Athena, Databricks, Redshift, BigQuery, ClickHouse, MySQL / generic SQL, Snowflake.

Other sources Ingest connects for SaaS teams: Asana, Salesforce, Airtable, Clockify, Facebook Ads, Frankfurter.

Get Jira data into your warehouse

Last updated 2026-10-16.