BugSnag connector
Set up the BugSnag connector in Kaivo: authentication, configuration, the 13 BigQuery tables it syncs, and answers to common questions.
Written By Lauri Raivio
Last updated 16 days ago
Kaivo is a fully managed data platform that syncs your BugSnag data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from BugSnag instead of moving it.
What is the BugSnag connector
Sync your Bugsnag error data into BigQuery with Kaivo to analyse stability and error trends across your projects.
Getting started with the BugSnag connector
- Sign up for Kaivo and create a workspace.
- Connect your BugSnag account.
- Choose which tables to sync.
- Wait for the initial sync to finish.
- Query your data in BigQuery or your favourite AI or BI tool.
Authenticating BugSnag
Authenticate with your Auth Token.
Configuring the BugSnag connector
When you set up the connector, you provide:
Tables and columns synced from BugSnag
Kaivo syncs 13 tables from BugSnag into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
collaborators (18 columns)
collaborators (18 columns)
Subtable: collaborators__project_ids
Subtable: collaborators__team_ids
errors (27 columns)
errors (27 columns)
Subtable: errors__linked_issues
Subtable: errors__missing_dsyms
Subtable: errors__release_stages
event_fields (17 columns)
event_fields (17 columns)
Subtable: event_fields__filter_options__aliases
Subtable: event_fields__filter_options__match_types
Subtable: event_fields__filter_options__values
Subtable: event_fields__pivot_options__aggregates
Subtable: event_fields__pivot_options__fields
events (13 columns)
events (13 columns)
Subtable: events__exceptions
organizations (17 columns)
organizations (17 columns)
Subtable: organizations__billing_emails
pivots (8 columns)
pivots (8 columns)
Subtable: pivots__summary__list
projects (24 columns)
projects (24 columns)
Subtable: projects__discarded_app_versions
Subtable: projects__discarded_errors
Subtable: projects__global_grouping
Subtable: projects__location_grouping
Subtable: projects__release_stages
releases (16 columns)
releases (16 columns)
saved_searches (23 columns)
saved_searches (23 columns)
Subtable: saved_searches__additional_filtersets
saved_searches_usage_summary (6 columns)
saved_searches_usage_summary (6 columns)
supported_integrations (14 columns)
supported_integrations (14 columns)
Subtable: supported_integrations__fields
Subtable: supported_integrations__fields__allowed_values
Subtable: supported_integrations__issue_automation_options
Subtable: supported_integrations__issue_automation_options__error_fixed__options
Subtable: supported_integrations__issue_automation_options__error_reopened__options
Subtable: supported_integrations__issue_automation_options__issue_resolved__default_options
Subtable: supported_integrations__issue_automation_options__issue_resolved__options
Subtable: supported_integrations__issue_automation_options__issue_unresolved__default_options
Subtable: supported_integrations__issue_automation_options__issue_unresolved__options
teams (7 columns)
teams (7 columns)
trace_fields (8 columns)
trace_fields (8 columns)
Subtable: trace_fields__filter_options__match_types
Subtable: trace_fields__filter_options__values
How the BugSnag sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where BugSnag supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.
Frequently asked questions
How long does the initial sync take for BugSnag?
It depends on how much history is in your BugSnag account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.
Can I sync only some tables or columns?
Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.
What happens when BugSnag's schema changes?
New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in BugSnag, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.
How do I handle GDPR or data deletion requests?
Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in BugSnag instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the BugSnag connector in Kaivo and all of its synced data is deleted with it.
Common use cases for BugSnag data
Error trends
Use errors and events to track error volume and new issues over time.
Release stability
Join releases with errors to see how each release affects stability.
Project reliability
Group errors by project to find the apps that need the most attention.
Use BugSnag data in your AI and BI tools
Once BugSnag data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with BugSnag data.
Claude
Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →
Power BI
Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →
Data Studio
Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →
Tableau
The premium analytics standard, with native BigQuery integration. Setup guide →
Google Sheets
Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →
Excel
Connect via Power Query's BigQuery connector. Setup guide →
Metabase
Open-source BI tool with strong BigQuery support. Setup guide →
See our pricing page for BugSnag connector pricing and plan details.
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