Quickstart · Source connector
Salesforce ELT Connector
Extract brings Salesforce 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 Salesforce data to monitor recurring activity and investigate meaningful changes over time.
Cross-system analysis
Combine Salesforce data with customer, finance, and operational metrics for consistent reporting.
Data quality monitoring
Compare Salesforce record totals and reporting periods to identify incomplete or unexpected data.
Flexible reporting cadence
Refresh Salesforce reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Salesforce quickstart data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Connector data
Configured streams
Configure the API resources or reports to replicate when creating the Extract connection.
Schema
Data model at a glance
Connector pairings
Popular destinations
Commonly paired with Salesforce in Extract workflows.
Why Extract
Why Extract for Salesforce
- Rust-native performanceUse Rust-native data movement to refresh Salesforce reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Salesforce API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Salesforce 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 Salesforce 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. Dynamic stream configuration supports incremental changes. Behavior depends on stream settings. Extract records run details so teams can verify each sync.
Can I backfill historical Salesforce data with Extract?
Historical coverage for Salesforce: 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 Salesforce data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Salesforce 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 Salesforce?
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 Salesforce data model look like in the destination?
The Available streams table describes the datasets Extract can read from Salesforce. Use the connector documentation link for the available schema details and configuration requirements.