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Connect Google Play Store to Amazon Redshift

Connect Google Play Store to Amazon Redshift and export selected accounts, metrics, and dimensions to your Amazon Redshift 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 Amazon Redshift

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Google Play Store data in Amazon Redshift

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 Amazon Redshift tables up to date

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

Analysis

Keep your Amazon Redshift tables up to date

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

Google Play Store metrics and dimensions available in Amazon Redshift

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 Amazon Redshift in minutes

Move your data from Google Play Store to Amazon Redshift 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 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 Amazon Redshift destination

Enter the Redshift host, database, and credentials that Catchr should use. The connection is checked before the destination is saved.

Destination / Amazon Redshift Required fields
Host Required
reporting-cluster.abc123.eu-west-1.redshift.amazonaws.com
Username Required
catchr_loader
Password Required
••••••••••••
Database Required
marketing_warehouse
Step three

Keep your Amazon Redshift tables updated

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

Export job / Amazon Redshift Example
Schema Destination
marketing_raw
Table Per job
facebook_ads_daily
Recurring schedule Choose a cadence
Every 6 hours
Daily · 06:00
Weekly · Mon
First sync scheduledSelected fields · configured history
06:00 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

Connect more table to your Google Play Store data

Open the dedicated route for each platform. Its field catalog, reporting grain, historical constraints, and warehouse use cases should be specific to that source.

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Before you connect your first source.

Plain answers for marketers evaluating MCP and Catchr.

What does MCP stand for

MCP stands for Model Context Protocol. It is an open standard that lets AI applications connect to external data sources and tools through a common interface.

What is an MCP server?

An MCP server makes selected data or capabilities available to an MCP-compatible application. Catchr MCP acts as the bridge between your AI assistant and the marketing platforms connected to Catchr.

How is MCP different from an API?

An API exposes ways for software to exchange data or perform actions. MCP provides a standard designed for AI applications to discover and use those capabilities. Catchr handles the source APIs and exposes useful marketing-data capabilities through MCP.

Do I need to code to use Catchr MCP?

No. Connect your sources in Catchr, add the remote MCP server URL to a supported AI assistant, and complete authorization through the interface.

Does Catchr MCP work with ChatGPT and Claude?

Yes. Catchr provides dedicated setup guides for both. Custom MCP support can depend on your AI plan, your region, and your workspace administrator settings, so check the relevant guide before setup.

What can I ask about my marketing data?

You can request performance summaries, period comparisons, campaign and account breakdowns, anomaly investigations, and client-ready recaps. Precise prompts should include the account, date range, metrics, comparison, and desired output format.

Which data sources are available?

Catchr supports more than 100 platforms across advertising, analytics, CRM, ecommerce, email, SEO, and social. Explore the connector directory to confirm a specific source.

Still have a question ? 

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