Reverse ETL is a direction, not a product category by itself: data moving from the warehouse back out into the operational tools a team actually works in.
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Quick answer: Reverse ETL takes data that already lives in a warehouse and pushes it out to the tools people work in day to day, a CRM, an ad platform, a spreadsheet, which is the reverse of ETL or ELT, both of which load data into the warehouse in the first place. QueryFlow can push a query's results into Salesforce or Google Sheets on a schedule, which is reverse ETL in the narrow sense, but it doesn't carry the 100-plus SaaS-app catalog dedicated reverse-ETL platforms build their whole product around.
ETL and ELT both describe getting data into a warehouse: extract from a source, transform it (before or after loading, depending on which acronym), land it in Snowflake, BigQuery, or wherever your analytics live. Reverse ETL is the same idea running backwards. Instead of a source feeding the warehouse, the warehouse becomes the source, and the destination is an operational tool: a CRM field getting updated from a computed lifetime-value column, an ad platform's audience list getting refreshed from a warehouse segment, a support tool getting a customer's plan tier synced in from billing data that only lives in the warehouse.
The term exists because this direction of data movement has different requirements than loading a warehouse does. Operational tools have their own APIs, their own rate limits, and fields that business users edit directly, so writing into them safely usually means smaller, more frequent syncs than a nightly warehouse load, and more care about not overwriting a value a human just changed by hand.
QueryFlow's Data Sync can write a query's output into Salesforce or Google Sheets on a schedule, using Insert, Update, or Upsert with a MATCH ON key column, the same mechanics it uses for warehouse-to-warehouse syncs. Point a query at your BigQuery warehouse, map its columns to Salesforce fields, upsert on a customer ID, and you have a small reverse-ETL pipeline: warehouse data landing back in the CRM your sales team actually opens.
What it isn't is a reverse-ETL platform in the category sense. Dedicated tools like Census and Hightouch build their product around a large catalog of SaaS destinations, each with app-specific field mappings and API quirks already handled, plus dependency tracking across models. QueryFlow covers Salesforce and Google Sheets as destinations, alongside its warehouse and file targets, which handles a real slice of reverse-ETL use cases without trying to be the general-purpose version of the category.
A common one: compute a lead score in the warehouse from marketing and product-usage data, then push it into Salesforce so reps see it on the lead record without needing warehouse access themselves.
SELECT lead_id, score FROM `project.marketing.lead_scores` WHERE updated_at >= CURRENT_TIMESTAMP() - INTERVAL 1 DAY;
In Data Sync, that BigQuery query becomes the source, Salesforce's Lead object the target, lead_id mapped to the matching Salesforce ID field as MATCH ON, and Upsert as the mode so new scores update existing leads without touching anything else on the record.
If your list of destinations grows past Salesforce and Sheets, you need warehouse data landing in Zendesk, Intercom, and a paid-ads platform too, a dedicated reverse-ETL tool's connector catalog will save real time over building each one by hand. QueryFlow is the right fit when the destination list is short and you'd rather not add a second vendor for it.
Related: sync Postgres into Salesforce, Salesforce into Google Sheets, and QueryFlow as a reverse-ETL tool for Mac for the fuller feature rundown.
Overlapping, not identical. Data Sync moves data in either direction between any two connections; reverse ETL specifically describes the warehouse-to-operational-tool direction, which Data Sync covers when the target is Salesforce or Google Sheets.
No. Its destinations are Salesforce, Google Sheets, the supported warehouses, and file/notification outputs. It doesn't carry a broad SaaS-app connector catalog the way dedicated reverse-ETL platforms do.
No, opposite direction. ELT loads a source into a warehouse and transforms it there. Reverse ETL takes data already in the warehouse and pushes it back out.
It can, if the sync's mapped fields include one a rep also edits by hand and the sync runs after their edit. Mapping only the fields the warehouse should own, and scheduling around when reps are actively working the record, are the usual mitigations.
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