RevenueCat connector

Kaivo is a fully managed data platform that syncs your RevenueCat 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 payment and finance data instead of moving it.

What is the RevenueCat connector

Sync your RevenueCat subscription data into BigQuery with Kaivo to analyse in-app subscriptions, revenue, and churn.

Getting started with the RevenueCat connector

1. Sign up for Kaivo and create a workspace.
2. Connect your RevenueCat account.
3. Choose which tables to sync.
4. Wait for the initial sync to finish.
5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating RevenueCat

Authenticate with your API Key.

Configuring the RevenueCat connector

When you set up the connector, you provide:

Tables and columns synced from RevenueCat

Kaivo syncs 15 tables from RevenueCat into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

How the RevenueCat sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where RevenueCat 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 RevenueCat?

It depends on how much history is in your RevenueCat 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 RevenueCat'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 RevenueCat, 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 RevenueCat 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 RevenueCat connector in Kaivo and all of its synced data is deleted with it.

Common use cases for RevenueCat data

Recurring revenue

Use customers_subscriptions and metrics_overview to track recurring revenue and churn over time.

Entitlement analysis

Join entitlements with offerings to see which plans drive revenue.

Customer view

Use customers and customers_purchases to measure lifetime value.

Use RevenueCat data in your AI and BI tools

Once RevenueCat 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 RevenueCat 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 RevenueCat connector pricing and plan details.

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