Marketing · Source connector
Galaxy Store ELT Connector
Extract brings Galaxy Store marketing data into data warehouses and databases for analysis with the rest of your business data. Teams use it to compare channel performance, audience engagement, and campaign trends. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Marketing performance analysis
Compare Galaxy Store channel, campaign, and engagement trends to identify opportunities for improvement.
Audience and content analysis
Use Galaxy Store data to understand which audiences, content, and activities contribute to engagement.
Cross-channel reporting
Combine Galaxy Store metrics with other marketing and business data for consistent performance reporting.
Flexible reporting cadence
Refresh Galaxy Store reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Galaxy Store marketing data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Connector data
Available streams
| Stream | Description | Sync mode |
|---|---|---|
daily_ratings_by_country | Fields include content_id, country, date, daily_rat_score. | Incremental |
daily_downloads_sales_by_device | Fields include content_id, date, device, revenue_iap_order_count. | Incremental |
daily_seller_metrics_by_device | Fields include date, device, revenue_iap_order_count, revenue_total. | Incremental |
daily_ratings_by_device | Fields include content_id, date, device, daily_rat_score. | Incremental |
daily_downloads_sales_by_country | Fields include content_id, country, date, revenue_iap_order_count. | Incremental |
daily_seller_metrics_by_country | Fields include country, date, revenue_iap_order_count, revenue_total. | Incremental |
Schema
Data model at a glance
daily_ratings_by_country
content_idstringcountrystringdatestringdaily_rat_scorenumberdaily_rat_volumenumber
daily_downloads_sales_by_device
content_idstringdatestringdevicestringrevenue_iap_order_countnumberrevenue_totalnumbertotal_unique_installs_filternumber
daily_seller_metrics_by_device
datestringdevicestringrevenue_iap_order_countnumberrevenue_totalnumbertotal_unique_installs_filternumber
daily_ratings_by_device
content_idstringdatestringdevicestringdaily_rat_scorenumberdaily_rat_volumenumber
daily_downloads_sales_by_country
content_idstringcountrystringdatestringrevenue_iap_order_countnumberrevenue_totalnumbertotal_unique_installs_filternumber
daily_seller_metrics_by_country
countrystringdatestringrevenue_iap_order_countnumberrevenue_totalnumbertotal_unique_installs_filternumber
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Galaxy Store in Extract workflows.
Why Extract
Why Extract for Galaxy Store
- Rust-native performanceUse Rust-native data movement to refresh Galaxy Store reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Galaxy Store API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Galaxy Store data with customer and finance models, then send approved outputs through a separately configured Reverse ETL destination.
FAQ
Frequently asked questions
How does Extract handle incremental and full Galaxy Store syncs?
An incremental sync processes only new or changed data since a stored checkpoint or new date partition, while a full sync processes the complete selected dataset or date range again. By avoiding repeated processing and writes for the full dataset, incremental syncs can reduce destination database updates and warehouse compute costs. Stream schemas define partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Galaxy Store data with Extract?
Historical coverage for Galaxy Store: Backfill (Days) (backfill): The backfill setting revisits and updates data from the past X days, ensuring the most current and accurate information replaces any previously pulled data. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Galaxy Store data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Galaxy Store API activity, execution steps, and timing. This helps teams distinguish a source-data delay from a failed or incomplete run.
How often can Extract sync data from Galaxy Store?
Extract supports schedules every 15 minutes, hourly, daily, or on a custom cadence. Teams can choose a frequency that matches routine reporting, time-sensitive monitoring, or operational activation needs.
What does the Galaxy Store data model look like in the destination?
The Available streams table describes the datasets Extract can read from Galaxy Store. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.