Canny connector
Set up the Canny connector in Kaivo: authentication, configuration, the 10 BigQuery tables it syncs, and answers to common questions.
Written By Lauri Raivio
Last updated 15 days ago
Kaivo is a fully managed data platform that syncs your Canny 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 customer support data instead of moving it.
What is the Canny connector
Sync your Canny feedback data into BigQuery with Kaivo to analyse feature requests and customer feedback across your boards.
Getting started with the Canny connector
- Sign up for Kaivo and create a workspace.
- Connect your Canny 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 Canny
Authenticate with your API Key.
Tables and columns synced from Canny
Kaivo syncs 10 tables from Canny into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
boards (10 columns)
boards (10 columns)
categories (12 columns)
categories (12 columns)
changelog_entries (12 columns)
changelog_entries (12 columns)
Subtable: changelog_entries__labels
Subtable: changelog_entries__posts
Subtable: changelog_entries__types
comments (31 columns)
comments (31 columns)
Subtable: comments__image_ur_ls
Subtable: comments__mentions
Subtable: comments__post__image_ur_ls
Subtable: comments__post__jira__linked_issue_i_ds
Subtable: comments__post__jira__linked_issues
Subtable: comments__post__tags
companies (12 columns)
companies (12 columns)
posts (43 columns)
posts (43 columns)
Subtable: posts__clickup__linked_tasks
Subtable: posts__custom_fields
Subtable: posts__image_ur_ls
Subtable: posts__jira__linked_issue_i_ds
Subtable: posts__jira__linked_issues
Subtable: posts__merge_history
Subtable: posts__tags
status_changes (27 columns)
status_changes (27 columns)
Subtable: status_changes__post__image_ur_ls
Subtable: status_changes__post__jira__linked_issue_i_ds
Subtable: status_changes__post__jira__linked_issues
Subtable: status_changes__post__tags
tags (12 columns)
tags (12 columns)
users (11 columns)
users (11 columns)
Subtable: users__companies
votes (34 columns)
votes (34 columns)
Subtable: votes__post__image_ur_ls
Subtable: votes__post__jira__linked_issue_i_ds
Subtable: votes__post__jira__linked_issues
Subtable: votes__post__tags
How the Canny sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Canny 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 Canny?
It depends on how much history is in your Canny 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 Canny'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 Canny, 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 Canny 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 Canny connector in Kaivo and all of its synced data is deleted with it.
Common use cases for Canny data
Feature demand
Use posts and votes to find the most requested features across your boards.
Feedback themes
Join posts with categories and tags to understand what customers ask for.
Roadmap tracking
Use status_changes and changelog_entries to follow requests from idea to shipped.
Account context
Join posts with companies to see which customers drive demand.
Use Canny data in your AI and BI tools
Once Canny 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 Canny 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 Canny connector pricing and plan details.
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