Pipeliner connector

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

Written By Lauri Raivio

Last updated About 4 hours ago

Kaivo is a fully managed data platform that syncs your Pipeliner 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 CRM data instead of moving it.

What is the Pipeliner connector

Sync your Pipeliner CRM data into BigQuery with Kaivo to report on pipeline, accounts, and forecasts in one place.

CategoryCRM
StatusGenerally available
AuthenticationUsername and password
SetupSelf-service

Getting started with the Pipeliner connector

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

Connect with your Pipeliner login. You provide:

FieldDescription
Password

The API password paired with the token above (shown only once when you generate your API keys).

Configuring the Pipeliner connector

When you set up the connector, you provide:

FieldDescription
Username

The API token for your Pipeliner space, used as the Basic auth username. Generate API keys under Sales Pipeline β†’ API Access in the Pipeliner customer portal.

Data Center

The data center region hosting your Pipeliner space.

Space ID

Your Pipeliner Space ID, shown when you obtain API Access; it identifies the space to sync from.

Tables and columns synced from Pipeliner

Kaivo syncs 24 tables from Pipeliner into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

How the Pipeliner sync works

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

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

Common use cases for Pipeliner data

Pipeline reporting

Use leads and lead_oppties to track pipeline value and conversion over time.

Forecasting

Use forecasts and entity_scorings to build a clearer view of expected revenue.

Account view

Join accounts with contacts and activities to understand your customers.

Use Pipeliner data in your AI and BI tools

Once Pipeliner 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 Pipeliner data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide β†’

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide β†’

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 β†’

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide β†’

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide β†’

Excel

Connect via Power Query's BigQuery connector. Setup guide β†’

Metabase

Open-source BI tool with strong BigQuery support. Setup guide β†’

See our pricing page for Pipeliner connector pricing and plan details.