Jira Cloud Connector
Sync Jira Cloud issues (with components, subtasks, transitions, comments, worklogs, and changelog), projects, users, and workflows into your warehouse.
Evaluating against Fivetran? See how Supaflow handles Jira Cloud pricing, connector quality, and Snowflake deployment side-by-side.
Supaflow vs FivetranWhy Supaflow
All connectors included
Every connector is available on every plan. Pricing does not increase with connector count.
Pay for compute, not rows
Credit-based pricing. Usage scales with your pipelines, not with row counts.
One platform
Ingestion, dbt Core transformation, reverse ETL, and orchestration in a single workspace.
Capabilities
Email + API Token Authentication
Basic auth with your Atlassian email and an API token from id.atlassian.com. No OAuth flow needed. The connector is read-only and never writes back to Jira; the account only needs Browse Projects permission on the projects you want to sync.
Incremental Issues by `updated`
Issues sync incrementally on the `updated` field, using a JQL query that bounds `updated >= last_cursor AND updated < now`. Jira JQL only supports minute-level precision; the connector truncates cursors to minutes and persists the truncated value as state so boundary updates are never silently missed.
Custom Field Registry Integration
On each schema refresh, the connector pulls `/rest/api/3/field` to discover every standard and custom field on your Jira site, with the type Atlassian declares for each. That prevents dlt from silently dropping columns whose values happen to be null in the sampled batch -- fields like `duedate`, `resolutiondate`, `assignee`, and time tracking survive even on small syncs.
Nine Child Tables on Issues
The issues resource materializes nine child tables for components, fix versions, versions, issue links, subtasks, transitions, comments, worklogs, and changelog histories. Pick which children to materialize in the schema wizard -- unselected children are skipped, and the connector uses Jira’s `fields` and `expand` parameters to push selection down to the API.
Field Pushdown for Large Sites
When you narrow the issue fields to sync, the connector reverse-maps your selections through the Jira field registry and passes them as `fields=<list>` on each API call. Required internal fields (`id`, `key`, `updated`, `self`) are always included. Response payloads are smaller and sync time drops on large sites.
Lookback for Eventual Consistency
Optional per-sync Lookback Period (seconds) rolls the cursor back by that many seconds before querying Jira. Useful if you observe late-arriving issue updates due to Jira Cloud’s eventual consistency. Set it to 60--300 seconds if you see occasional misses.
Supported Objects
Top-level Resources
issues
Incremental by `updated`. Powers nine child tables (components, fix versions, issue links, subtasks, transitions, comments, worklogs, changelog histories).
projects
Full refresh. All projects visible to the authenticated account.
users
Full refresh. Includes inactive accounts. Primary key is `account_id`.
workflows
Full refresh. Workflow definitions with a composite primary key of `id__entity_id` + `id__name`.
Issues Child Tables
issues__components
Components attached to issues (from `fields.components[]`).
issues__fix_versions
Fix version links (from `fields.fixVersions[]`).
issues__versions
Affected version links (from `fields.versions[]`).
issues__issuelinks
Inter-issue links (from `fields.issuelinks[]`).
issues__subtasks
Subtask references (from `fields.subtasks[]`).
issues__transitions
Available transitions (from `expand=transitions`).
issues__comment__comments
Comments on issues (from `fields.comment.comments[]`).
issues__worklog__worklogs
Worklog entries on issues (from `fields.worklog.worklogs[]`).
issues__changelog__histories
Issue history / changelog entries (from `expand=changelog`).
Not synced in v1
boards, sprints, epics as entity, filters, dashboards, permission schemes, notification schemes, issue types as entity, priorities, resolutions, project roles
Not exposed by the v1 connector. Jira Server and Data Center (self-hosted Jira) are also not supported -- the connector targets `*.atlassian.net` only. Email support@supa-flow.io with the endpoints you need.
How It Works
Create an Atlassian API token
Sign in to id.atlassian.com/manage-profile/security/api-tokens with the Atlassian account you want the connector to use. Click Create API token, give it a label like "Supaflow integration", and copy the token once -- Atlassian will not show it again.
Enter the subdomain and credentials in Supaflow
Enter your Jira Cloud subdomain (either `mycompany` or `mycompany.atlassian.net`; the connector strips the suffix), the Atlassian account email, and the API token. Credentials are stored encrypted.
Configure advanced settings
Optionally set Schema Refresh Interval in minutes (default 0 means refresh before every run, right for sites with active custom-field work). Optionally set Lookback Period in seconds to re-fetch a trailing window on each incremental run.
Test and save
Click Test & Save. Supaflow validates the credentials by calling `/rest/api/3/myself` with basic auth. On success the source is saved and schema discovery runs.
Use Cases
Engineering velocity and cycle-time reporting
Land issues and the changelog histories child table, then reconstruct status-transition timestamps in dbt to compute lead time, cycle time, and throughput per project or team.
Issue and worklog time tracking
Sync the worklog child table alongside issues to build time-by-project or time-by-assignee reports, even when your Jira license is Team-Managed and the in-product time-tracking views are limited.
Comment and mention analysis
The comments child table lands every comment body, author, and timestamp. Combine with LLM enrichment in the warehouse to classify customer-support issue comments, flag escalation language, or summarize long threads.
Frequently Asked Questions
Does Supaflow support Jira Server or Jira Data Center?
How does Supaflow handle Jira custom fields?
What permissions does the Atlassian account need?
Can I sync boards, sprints, epics, or filters?
How does incremental sync handle Jira’s JQL minute precision?
Does the connector handle Jira rate limits?
Can I run the Jira pipeline natively inside Snowflake?
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