Real-time
Two-way sync
Changes in Atlassian or BigQuery instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Data warehouse
Atlassian to BigQuery integration — real-time, two-way sync
Keep Atlassian and BigQuery in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Atlassian and BigQuery
Get the data locked inside Atlassian into BigQuery as live tables, and send results back where Atlassian can use them, without writing a pipeline.
Whatever Atlassian is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
Stacksync syncs Confluence Pages, Confluence Spaces, Jira Issues, Jira Projects from Atlassian into tables in BigQuery continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in BigQuery can also be written back into fields in Atlassian where the tool can use them.
Common use cases
- Create Jira issues from records in other systems, such as onboarding tasks generated from a closed-won CRM deal.
- Keep Jira and a second tracker (for example a customer's Jira instance) aligned during co-delivery projects.
- Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
- Feed ML feature tables in BigQuery from operational systems on a continuous schedule
History that outlives the tool
A continuously synced copy in BigQuery preserves a queryable record even as data ages out of Atlassian or gets changed inside it.
Analytics on Atlassian's data
Records and events from Atlassian land in BigQuery as queryable tables, current within seconds and ready to join with the rest of the warehouse.
Cross-tool reporting
Combine Atlassian's data with data from every other synced system to answer questions no single tool can.
What you can sync between Atlassian and BigQuery
Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.
| Atlassian objects | BigQuery objects | |
|---|---|---|
| Jira Projects Containers that scope issues, workflows, and permissions for a sync. | Tables The syncable unit: only tables can be synced per the Stacksync docs. | |
| Boards and Sprints Agile structures read to report on sprint contents and status. | Partitioned tables Synced like regular tables; partition columns map to target fields. | |
| Issue Comments Threaded discussion synced into linked tickets in external systems. | Clustered tables Supported; clustering is transparent to the sync. | |
| Attachments Files on issues mirrored to paired records where needed. | Datasets Organizational container — you pick which dataset’s tables to sync. | |
| Custom Fields Instance-specific fields (customfield IDs) that carry most business-specific data in syncs. | Projects Connection scope: the service account grants access per project. |
What ships with Atlassian ⇄ BigQuery
Connect Atlassian and BigQuery for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Atlassian–BigQuery connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Atlassian or BigQuery data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single Atlassian or BigQuery record.
Observability
Monitoring
Track your Atlassian ⇄ BigQuery sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Atlassian and BigQuery.
How the Atlassian and BigQuery connectors work
Atlassian
- Integration surface
- REST APIs per product (Jira Cloud and Confluence Cloud)
- Authentication
- OAuth 2.0 (3LO) for apps or API tokens with basic auth for scripts
- Change detection
- Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill
- Capabilities
- read · write · webhooks
BigQuery
- Integration surface
- GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
- Authentication
- Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
- Change detection
- Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
- Capabilities
- read · write · CDC
- Rate limits
- Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
How it works
How to connect Atlassian to BigQuery — three steps, no code
Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.
- 01
Connect your apps
Authenticate Atlassian and BigQuery with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Atlassian
connected
BigQuery
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Atlassian and BigQuery objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.
objects · Atlassian ⇄ BigQueryCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Atlassian BigQueryCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Atlassian and BigQuery integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Atlassian and BigQuery: authenticate both systems, choose the objects to sync (such as Atlassian's Jira Projects and Boards and Sprints), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Atlassian: Each Atlassian product has its own REST API and resource model; a sync spanning Jira and Confluence talks to separate endpoints under one Atlassian identity. BigQuery: The Storage Write API supports high-throughput streaming ingestion, which suits continuous sync loads better than legacy streaming inserts. Stacksync's field mapping accounts for these differences between Atlassian and BigQuery without custom code.
-
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Atlassian and BigQuery records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Atlassian and BigQuery connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Atlassian–BigQuery integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Atlassian and BigQuery. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Atlassian: Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill. On BigQuery: Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
SECURITY
Security teams love Stacksync
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Atlassian and BigQuery.
Popular · 8 of 386
-
Atlassian ⇄ Databricks -
Atlassian ⇄ AWS S3 -
Atlassian ⇄ Actian Vector -
Atlassian ⇄ Amazon Redshift -
BigQuery ⇄ SendGrid -
BigQuery ⇄ Twilio -
BigQuery ⇄ GitHub -
BigQuery ⇄ Braze
No integrations match .
