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Connect Google Play Store to Snowflake

Connect Google Play Store 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 Google Play Store API pipeline.

Used by the world's leading companies

Export Google Play Store data to Snowflake

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Google Play Store data in PostgreSQL

Bring all your Google Play Store 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 Google Play Store so every dashboard, model, and report works with fresh information.

Analysis

Unify Google Play Store with the rest of your business data

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

Google Play Store metrics and dimensions available in Snowflake

Access 27 metrics and 53 dimensions from Google Play Store connectors including Store listing conversion rate, Store listing acquisitions, Store listing visitors, Daily User Installs, Daily User Uninstalls, Active Subscriptions, Amount, Total Average Rating, Date, Traffic Source, Search Term, UTM campaign, UTM Source, Country, Package Name, SKU Id and many more...

27

Metrics availables

53

Dimensions availables

Connect Google Play Store to Snowflake in minutes

Move your data from Google Play Store 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 Google Play Store account

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

Client A · Connected sources
5 sources ready
Google Play Store Google Play Store 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

Review 30-day Google Play Store app growth performance in SQL.

This example summarizes downloads, installs, revenue, and install rate by application.

Google Play Store.sql
BigQuery SQL
30-day window
SELECT
  app_name,
  SUM(downloads) AS downloads,
  SUM(installs) AS installs,
  SUM(revenue) AS revenue,
  SAFE_DIVIDE(
    SUM(installs),
    SUM(downloads)
  ) AS install_rate
FROM `your_project.marketing_raw.google_play_store_app_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY app_name
ORDER BY downloads DESC;
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.

What is required to populate Snowflake with Google Play Store data?

Connect Google Play Store as a Catchr source. Add your existing Snowflake database, create a datastream, and configure a job that writes the selected fields to the "apps" table.

What Google Play Store data is available for a Snowflake job?

Select concrete Google Play Store fields such as Active Subscriptions, Amount, Canceled Subscriptions, and Day of the month. You can rename the chosen columns, preview the result, and write them to Snowflake tables such as apps, app versions, and downloads.

How often can Catchr refresh Google Play Store data in Snowflake?

Catchr first processes the historical range configured for Google Play Store. Later runs update the "apps" table using the saved frequency and rolling import window.

How should I configure row updates for Google Play Store in Snowflake?

Catchr uses the selected partition field to refresh the relevant Google Play Store period inside "apps". Leaving it blank changes the job to append-only behavior.

What can I query once Google Play Store data is available in Snowflake?

With Google Play Store data, a Snowflake query can summarize downloads, installs, revenue, and install rate by application. A Snowflake view comparing Active Subscriptions and Amount can feed agency dashboards or downstream BI models.

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 ? 

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