Data pipelines

Contents

Data pipelines is PostHog's customer data platform. It pulls data in from the tools you already use, lets you filter and reshape events as they're ingested, and sends the result wherever it needs to go – in realtime or on a schedule.

Everything runs on the same event stream that powers the rest of PostHog, so the data you send to Slack, your warehouse, or your CRM is the data you analyze. Pipelines are built from Hog functions, which you can configure from a template, write yourself, or have PostHog AI write for you.

Get started

Where you can use it

Build and monitor pipelines in the PostHog web app, or create and debug functions from an MCP client or your own systems.

PostHog Web

Configure sources, transformations, and destinations, then watch logs and metrics for each one.

Build a pipeline →

PostHog MCP

Create, update, test-invoke, and debug pipeline functions from any MCP client or AI editor.

Manage pipelines →

API

Manage Hog functions and batch exports programmatically, so pipelines live in your own config.

Use the API →

Where its data comes from

Data pipelines runs on the events and person data already in your PostHog project, plus whatever you connect from outside it. Sources bring data in, transformations reshape it during ingestion, and destinations carry it back out.

Sources

Sync data from hundreds of tools, or push it in yourself with an incoming webhook.

Link a source →

Transformations

Add, edit, or drop event properties during ingestion, before anything is stored.

Transform events →

Destinations

Send events onward as they happen, or in scheduled batches to your warehouse.

Send data out →

Common use cases

Teams most often use data pipelines to keep a warehouse in sync with product data, to push events into tools like Slack, HubSpot, or Intercom over webhooks, and to enforce a schema at ingestion so bad events never make it into analytics.

Transformations also help you label events on the way in – setting a property like user_tier or page_category – which makes downstream metrics and SQL queries much easier to write.

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