pages
13 fields- Primary key
- id
- Some of the fields
idauthorIdcreatedAtlastOwnerId_linksownerIdparentIdparentTypepositionspaceIdstatustitleand 1 more
Confluence + BigQuery
Erathos connects Confluence to BigQuery so your Atlassian wiki stops being a knowledge silo. The native connector authenticates with your site subdomain and an Atlassian API token, then syncs spaces, pages, blogposts, attachments, footer and inline comments, labels, and tasks into BigQuery as query-ready tables, preserving relationships between spaces, pages, and nested content.
With wiki data next to the rest of your warehouse, you can cross page activity with product, support, or CRM sources, audit content coverage by space and label, and run ad hoc queries over versions, comments, and tasks without manual exports.
14-day free trial. No credit card required.
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Simplified extraction and ingestion
Move data in a few clicks
Connect your source
Authenticate your account and you're done. 100+ ready-made connectors, no code required.
Configure the sync
Pick the tables, the schedule and the update type: batch, cursor-based incremental or CDC.
Choose your destination
Load into BigQuery, Redshift, Databricks, PostgreSQL, ClickHouse, Amazon S3 and more.
Available data
What Confluence sends to BigQuery
63 Confluence tables can be synced to BigQuery. Each table is created in BigQuery with the same name it has in the connector, inside the schema you choose when setting up the connection.
A closer look at some tables
blogposts
10 fields- Primary key
- id
- Some of the fields
idauthorIdcreatedAtlastOwnerId_linksownerIdspaceIdstatustitleversion
spaces
10 fields- Primary key
- id
- Some of the fields
idauthorIddescriptionhomepageIdiconkey_linksnamestatustype
A first query in BigQuery
Reading the Confluence pages table straight from BigQuery. Replace your_schema with the schema you chose for the connection.
SELECT
id,
`authorId`,
`createdAt`,
`lastOwnerId`
FROM your_schema.pages
LIMIT 10Available tables
attachment_detail· under attachmentsattachment_operations· under attachmentsattachment_properties· under attachmentsattachment_versions· under attachmentsattachmentsattachments_footer_comments· under attachmentsattachments_labels· under attachmentsblogpost_detail· under blogpostsblogpost_labels· under blogpostsblogpost_likes_count· under blogpostsblogpost_likes_users· under blogpostsblogpost_operations· under blogpostsblogpost_properties· under blogpostsblogpost_versions· under blogpostsblogpostsblogposts_attachments· under blogpostsblogposts_footer_comments· under blogpostsblogposts_inline_comments· under blogpostsclassification_levelsfooter_comment_children· under footer_commentsfooter_comment_likes_count· under footer_commentsfooter_comment_likes_users· under footer_commentsfooter_comment_operations· under footer_commentsfooter_comment_versions· under footer_commentsfooter_commentsinline_comment_children· under inline_commentsinline_comment_likes_count· under inline_commentsinline_comment_likes_users· under inline_commentsinline_comment_operations· under inline_commentsinline_comment_versions· under inline_commentsinline_commentslabel_attachments· under labelslabel_blogposts· under labelslabel_pages· under labelslabelspage_detail· under pagespage_labels· under pagespage_likes_count· under pagespage_likes_users· under pagespage_operations· under pagespage_properties· under pagespagespages_ancestors· under pagespages_attachments· under pagespages_children· under pagespages_descendants· under pagespages_direct_children· under pagespages_footer_comments· under pagespages_inline_comments· under pagespages_versions· under pagesspace_detail· under spacesspace_labels· under spacesspace_operations· under spacesspace_permission_assignments· under spacesspace_permissionsspace_properties· under spacesspace_role_assignments· under spacesspace_rolesspacesspaces_blogposts· under spacesspaces_content_labels· under spacesspaces_pages· under spacestasks
What Is Erathos?
Consolidating Confluence data in BigQuery has never been easier
Erathos is a data ingestion platform built for teams that need reliability, visibility, and control. With the Confluence connector, you can automatically move spaces, pages, blogposts, comments, labels, and tasks into BigQuery, with full observability into every run and zero maintenance.
Why do data teams choose Erathos for Confluence?
Data in your data warehouse in minutes
Confluence connector ready to use
Connect Confluence to BigQuery in minutes with our native connector. Authenticate with your site subdomain and an Atlassian API token, then sync spaces, pages, blogposts, attachments, comments, labels, and tasks automatically, with no code required.
Learn moreTotal control over your Confluence pipelines
Configure schedule, frequency, and sync type at the table level. Most Confluence streams run as full refresh, while streams like tasks sync incrementally with a createdAt cursor, keeping your BigQuery costs low and predictable.
Learn moreEnd-to-end observability
Stop finding out about failures only when the business team complains. Every run is logged with runtime, processed rows, and error context. Automatic alerts via Slack, Discord, or email as soon as anything goes off track.
Learn more14-day free trial. No credit card required.
Our partners
Building data-driven stories
“Every new source implementation, if I had to do it myself, would take about two or three months. With Erathos, it's done in a few hours. I don't need the skills of a data engineer to generate real value from the company's data.”
Bruno RossoData Analyst, Brick Software
“Erathos revolutionized data management at WE. By integrating multiple SaaS tools into a single DW, our technical team now focuses on the core business. We implemented dashboards with insights across every area, enriching our organizational culture and improving our decision-making.”
Matheus NunesCTO & co-founder, WePayments
“We used to have a lot of rework, and now we don't. It's more efficient to work this way. If it's not your core business, hire Erathos. Spend your time modeling your own domain, not someone else's.”
Carlos SchwabeCo-Founder & CDO, Brick
“If I didn't have this infrastructure, I'd need three or four people to do what Erathos does today. I was able to generate real value from my data with a much leaner setup than I thought I'd need. That's the core of building a data-driven culture: the team only uses data when they can trust it.”
Thiago PazCFO, Brick
“Erathos brought a practical turnaround at CCM. We were able to integrate financial systems, CRM, and processes with BigQuery in just a few clicks, with no technical team required. That gave us a reliable data warehouse that powers automations, dashboards, and even our customer service bots.”
Gustavo LoforteTechnology Manager, CCM Group
“The robustness and efficiency of Erathos's connectors — whether for Meta, Google, RD Station, or ERPs like Bling and Conta Azul — make the whole process much faster and more reliable. The technical documentation is extremely well put together and intuitive, which makes implementation much easier.”
Sayuri ValenteProject Manager, Xperiun
Explore
Other paths for your data
Other destinations for Confluence
Other sources that land in BigQuery
CRMs, ERPs, ad platforms and databases, all through the same managed pipeline.
FAQ
Frequently Asked Questions
Erathos is a data ingestion platform built for reliability, transparency, and control. We help data teams connect their SaaS tools, such as Confluence, to their data warehouse, without the maintenance cost of in-house pipelines or the opacity of traditional ETL tools. Setup takes minutes: name the connection, enter your Confluence site subdomain, and paste an Atlassian API token generated in your Atlassian account. Our customers reduce pipeline maintenance by up to 80%.
Spaces, pages, blogposts, attachments, footer and inline comments, labels, and tasks, plus nested structures like page versions, likes, properties, space permissions, space roles, and classification levels. That is over 60 streams, delivered with their relationships preserved so the data is ready for joins on arrival.
You can configure sync frequency at the table level, from every 5 minutes up to once per day. Most Confluence streams run as full refresh, while streams that support it, such as tasks, sync incrementally with a createdAt cursor, keeping the pipeline efficient and BigQuery costs predictable.
Erathos automatically detects failures and sends alerts to your email, Slack, or Discord with full execution context, not just 'job failed.' Smart retries handle transient errors, and every run is logged so your team can debug in minutes, not hours.
Yes. Every Erathos connector includes a 14-day free trial. Connect Confluence to BigQuery and start syncing immediately, no credit card required.