Quickstart · Source connector
Instagram ELT Connector
Extract brings Instagram quickstart data into data warehouses and databases for analysis with the rest of your business data. Teams use it to build recurring reporting and compare business activity across systems. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Business performance reporting
Use Instagram data to monitor recurring activity and investigate meaningful changes over time.
Cross-system analysis
Combine Instagram data with customer, finance, and operational metrics for consistent reporting.
Data quality monitoring
Compare Instagram record totals and reporting periods to identify incomplete or unexpected data.
Flexible reporting cadence
Refresh Instagram reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Instagram quickstart 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 |
|---|---|---|
lifetime_media_insights_by_story_navigation_action_type | Fields include id, story_navigation_action_type, _singular_extract_timestamp, navigation. | Full refresh |
ig_media | Fields include id, _singular_extract_timestamp, boost_ads_list, boost_eligibility_info.is_eligible. | Full refresh |
media_insights | Fields include id, _singular_extract_timestamp, comments, follows. | Full refresh |
user_insights_daily | Fields include id, date, _singular_extract_timestamp, accounts_engaged. | Incremental |
user_daily_insights_by_follow_type | Fields include id, date, follow_type, _singular_extract_timestamp. | Incremental |
lifetime_media_insights_by_action_type | Fields include id, action_type, _singular_extract_timestamp, profile_activity. | Full refresh |
media_comments | Fields include id, media_id, _singular_extract_timestamp, from.id. | Full refresh |
user_daily_insights_by_media_product_type | Fields include id, date, media_product_type, _singular_extract_timestamp. | Incremental |
user_daily_insights_by_contact_button_type | Fields include id, contact_button_type, date, _singular_extract_timestamp. | Incremental |
ig_user | Fields include id, _singular_extract_timestamp, biography, followers_count. | Full refresh |
Schema
Data model at a glance
lifetime_media_insights_by_story_navigation_action_type
idstringstory_navigation_action_typestring_singular_extract_timestampstringnavigationinteger
ig_media
idstring_singular_extract_timestampstringboost_ads_listjsonboost_eligibility_info.is_eligiblebooleanboost_eligibility_info.reasonstringcaptionstringcomments_countintegercopyright_check_information_statusstring
media_insights
idstring_singular_extract_timestampstringcommentsintegerfollowsintegerig_reels_avg_watch_timeintegerig_reels_video_view_total_timeintegerlikesintegernavigationinteger
user_insights_daily
idstringdatestring_singular_extract_timestampstringaccounts_engagedintegercommentsintegerlikesintegerprofile_links_tapsintegerreachinteger
user_daily_insights_by_follow_type
idstringdatestringfollow_typestring_singular_extract_timestampstringfollows_and_unfollowsinteger
lifetime_media_insights_by_action_type
idstringaction_typestring_singular_extract_timestampstringprofile_activityinteger
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Instagram in Extract workflows.
Why Extract
Why Extract for Instagram
- Rust-native performanceUse Rust-native data movement to refresh Instagram reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Instagram API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Instagram 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 Instagram 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 full refresh, partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Instagram data with Extract?
Historical coverage for Instagram: 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 Instagram data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Instagram 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 Instagram?
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 Instagram data model look like in the destination?
The Available streams table describes the datasets Extract can read from Instagram. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.