Railz connector

Set up the Railz connector in Kaivo: authentication, configuration, the 24 BigQuery tables it syncs, and answers to common questions.

Written By Lauri Raivio

Last updated About 3 hours ago

Kaivo is a fully managed data platform that syncs your Railz 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 Railz connector

Sync your Railz accounting data into BigQuery with Kaivo to analyse financial data from your connected accounting systems.

CategoryFinance & Payments
StatusGenerally available
AuthenticationAPI key
SetupSelf-service

Getting started with the Railz connector

  1. Sign up for Kaivo and create a workspace.
  2. Connect your Railz 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 Railz

Authenticate with your Secret Key.

FieldDescription
Secret Key

Your Railz API Secret Key, paired with the Client ID to authenticate to the Railz API. Keep it private.

Configuring the Railz connector

When you set up the connector, you provide:

FieldDescription
Client ID

Your Railz API Client ID, available in your Railz dashboard. Used together with the Secret Key to obtain an access token.

Start Date

Only data dated on or after this day will be synced.

Tables and columns synced from Railz

The available streams and columns depend on your account configuration (such as custom fields and objects), so they are determined when the connection runs rather than listed here.

How the Railz sync works

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

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

Common use cases for Railz data

Financial reporting

Use accounts and accounting_transactions to build reports across your books.

Receivables and payables

Join customers and vendors with bills to track what you owe and are owed.

Bank reconciliation

Use bank_accounts and bank_transfers to reconcile activity.

Use Railz data in your AI and BI tools

Once Railz 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 Railz 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 Railz connector pricing and plan details.