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Connect Appstore Review to Snowflake

Connect Appstore Review 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 Appstore Review API pipeline.

Used by the world's leading companies

Export Appstore Review data to Snowflake

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize App Store Review data in PostgreSQL

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

Analysis

Unify Appstore Review with the rest of your business data

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

Appstore Review metrics and dimensions available in Snowflake

Access 8 metrics and 21 dimensions from Appstore Review connectors including Average Rating, Rating, Review Count, One Star, Five Stars, Date, Review DateTime, Review Title, Review Text, Reviewer, Reply Text and many more...

8

Metrics availables

21

Dimensions availables

Connect Appstore Review to Snowflake in minutes

Move your data from Appstore Review 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 Appstore Review account

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

Client A · Connected sources
5 sources ready
Appstore Review Appstore Review 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 Appstore Review customer review performance in SQL.

This example summarizes review volume and average rating by location over the last 30 days.

App Store Review.sql
BigQuery SQL
30-day window
SELECT
  location_name,
  AVG(rating) AS average_rating,
  COUNT(*) AS reviews
FROM `your_project.marketing_raw.appstore_review_reviews`
WHERE review_date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY location_name
ORDER BY reviews 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.

How do I start a scheduled Appstore Review import into Snowflake?

Start with a connected Appstore Review source and an existing Snowflake database. Create a datastream between them, then configure the accounts, fields, schedule, and "locations" table.

Which Appstore Review entities can become Snowflake tables?

Select concrete Appstore Review fields such as Average Rating, Rating, Review Count, and Day of the year. You can rename the chosen columns, preview the result, and write them to Snowflake tables such as review sources, locations, and reviews.

Does Catchr support an initial fetch for Appstore Review data in Snowflake?

Set an initial fetch period for Appstore Review, then choose the frequency and lookback window for the job writing to "locations". Catchr rewrites that selected period on each run.

Which partition setting keeps Appstore Review Snowflake rows updated?

The partition field tells Catchr which Appstore Review rows in "locations" belong to the period being refreshed. If you omit it, every run appends records rather than updating them.

What is a practical SQL use case for Appstore Review data?

With Appstore Review data, a Snowflake query can summarize review volume and average rating by location over the last 30 days. A query built around Average Rating and Rating can support trend reviews, account comparisons, and operational reporting.

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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