Misc · Source connector
Google Calendar ELT Connector
Extract brings Google Calendar misc data into data warehouses and databases for analysis with the rest of your business data. Teams use it to build recurring reporting, investigate changes, and support operational decisions. 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 Google Calendar data to monitor recurring activity and investigate meaningful changes over time.
Cross-system analysis
Combine Google Calendar data with customer, finance, and operational metrics for consistent reporting.
Data quality monitoring
Compare Google Calendar record totals and reporting periods to identify incomplete or unexpected data.
Flexible reporting cadence
Refresh Google Calendar reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Google Calendar misc 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 |
|---|---|---|
calendar_list | Fields include id, access_role, background_color, deleted. | Full refresh |
event_attachment | Fields include event_id, file_id, file_url, icon_link. | Incremental |
event_entry_point | Fields include event_id, uri, access_code, entry_point_type. | Incremental |
event_attendee | Fields include event_id, email, additional_guests, comment. | Incremental |
allowed_conference_solution_type | Fields include calendar_list_id, solution_type. | Full refresh |
notification_setting | Fields include calendar_list_id, method, type. | Full refresh |
access_control_list | Fields include id, calendar_list_id, etag, role. | Full refresh |
event_reminder | Fields include event_id, method, minutes. | Incremental |
event | Fields include id, calendar_list_id, recurring_event_id, anyone_can_add_self. | Incremental |
default_reminder | Fields include calendar_list_id, method, minutes. | Full refresh |
Schema
Data model at a glance
calendar_list
idstringaccess_rolestringbackground_colorstringdeletedbooleandescriptionstringetagstringforeground_colorstringhiddenboolean
event_attachment
event_idstringfile_idstringfile_urlstringicon_linkstringmime_typestringtitlestring
event_entry_point
event_idstringuristringaccess_codestringentry_point_typestringlabelstringmeeting_codestringpasscodestringpasswordstring
event_attendee
event_idstringemailstringadditional_guestsintegercommentstringdisplay_namestringidstringoptionalbooleanorganizerboolean
allowed_conference_solution_type
calendar_list_idstringsolution_typestring
notification_setting
calendar_list_idstringmethodstringtypestring
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Google Calendar in Extract workflows.
Why Extract
Why Extract for Google Calendar
- Rust-native performanceUse Rust-native data movement to refresh Google Calendar reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Google Calendar API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Google Calendar 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 Google Calendar 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 Google Calendar data with Extract?
Historical coverage for Google Calendar: No connector-specific backfill parameter is exposed. Initial historical coverage depends on the stream and provider. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Google Calendar data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Google Calendar 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 Google Calendar?
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 Google Calendar data model look like in the destination?
The Available streams table describes the datasets Extract can read from Google Calendar. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.