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Connect PostHog to Snowflake

Connect PostHog to Snowflake and export selected accounts, metrics, and dimensions to your Google BigQuery project.

Configure the historical window, destination table, and recurring schedule without maintaining a PostHog API pipeline.

Used by the world's leading companies

Export PostHog data to Snowflake

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize PostHog data in PostgreSQL

Bring all your PostHog data into your warehouse and make it available for analytics, machine learning, and internal applications.

Data freshness

Keep your Snowflake tables up to date

Automatically sync new data from PostHog so every dashboard, model, and report works with fresh information.

Analysis

Unify PostHog with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

PostHog metrics and dimensions available in Snowflake

Access 1 metrics and 41 dimensions from PostHog connectors including Records, Event Name, Event Time, UTM Campaign, UTM Source, UTM Medium, Current Url, Pathname, Referrer, Country Code, City, Device Type, Browser and many more...

1

Metrics availables

41

Dimensions availables

Connect PostHog to Snowflake in minutes

Move your data from PostHog to Snowflake with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your PostHog account

Authenticate your PostHog account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Client A · Connected sources
5 sources ready
PostHog PostHog 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Choose the Snowflake destination

Add the account host, user, and database schema. Use a password for compatible users or a PEM private key for service accounts and stricter policies.

Destination / Snowflake Required fields
Authentication Choose one
Password
Key pair
Host Required
xy12345.eu-west-1
Username Required
catchr_service
Database Required
MARKETING.RAW
Private key passphrase Optional
••••••••••••
Private key Required for key pair
-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMw... -----END ENCRYPTED PRIVATE KEY-----
Step three

Keep your Snowflake tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example
Schema Destination
marketing_raw
Table Per job
linkedin_ads_daily
Recurring schedule Choose a cadence
Every 6 hours
Daily · 07:00
Weekly · Mon
First sync scheduledSelected fields · configured history
07:00 UTC

PostHog.sql
BigQuery SQL
30-day window
Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into Snowflake.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

Does my Snowflake database need to exist before I connect it?

Yes. Connect an existing Snowflake database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same Snowflake database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

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