QueryFlow processes data locally on your Mac. Your warehouse data stays in your warehouse. No SaaS vendor pulling your data into their cloud — no egress fees, no surprise AWS bills, no third-party processing.
AWS charges roughly $0.09/GB for data leaving its network. Snowflake charges egress fees for data leaving Snowflake-managed regions. Google Cloud charges $0.12/GB for cross-region transfers. These fees are usually invisible until they're not — at which point a $200/month bill is suddenly $2,000/month because some new ETL tool started replicating your warehouse to its own cloud for processing.
Cloud-based reverse ETL tools (Hightouch, Census, Fivetran reverse), cloud notebooks (Hex, Mode, Deepnote), and most modern cloud BI tools work by replicating your warehouse data to their cloud, processing it there, and delivering results. Every GB they pull from your warehouse triggers your cloud provider's egress meter. For high-volume use cases, the egress fees can rival or exceed the SaaS subscription cost.
QueryFlow runs the SQL directly in your warehouse, gets the result back to your Mac (which is small — typically thousands of rows, not millions), processes it locally, and writes to the destination directly. The warehouse is the compute engine. Your Mac is the orchestrator. Nothing sits in a third-party cloud.
A typical Snowflake-to-Salesforce sync of 50,000 customer records. Cloud reverse ETL approach: Snowflake exports the full 50,000 rows to the vendor's cloud (50MB), the vendor processes and pushes to Salesforce, charging you for the egress. QueryFlow approach: Snowflake runs the SELECT query, returns 50,000 rows directly to your Mac (still 50MB but going to localhost effectively from Snowflake's perspective if you're inside their network, or to a single endpoint), QueryFlow pushes to Salesforce. The data flow is more direct, the egress is the same single trip, and there's no intermediate vendor cloud.
The pain point is replication workloads. If you're using cloud SaaS to replicate Postgres tables to your warehouse every hour, you're paying egress fees every hour. If you're using cloud reverse ETL to push warehouse data to your CRM every 15 minutes, you're paying egress every 15 minutes. Local-first execution turns these recurring egress costs into one-time-per-run costs, with no intermediate cloud.
QueryFlow doesn't literally have zero egress — query results still have to travel from your warehouse to your Mac. But it eliminates the SaaS-vendor egress, which is the layer that compounds at scale. Your direct warehouse-to-Mac data transfer is usually free or negligible (especially if your Mac is reading from a database you own). The egress fees that disappear are the ones that go to a third-party cloud you don't control.
A team running 20 active SaaS-cloud pipelines (reverse ETL, cloud notebooks, BI replications) typically incurs $200-$2,000/month in cumulative egress fees they barely notice because they're spread across AWS, Snowflake, and Google Cloud invoices. Moving those workflows to QueryFlow's local-first model eliminates that recurring cost entirely. Combined with eliminating the SaaS subscriptions themselves, the total monthly savings often exceeds $1,000-$10,000 depending on team size.
Your cloud provider charges egress fees for data leaving their network. QueryFlow running on your Mac is technically 'outside' your warehouse's cloud, so query result transfer counts as egress. The difference vs cloud SaaS tools: QueryFlow doesn't add an extra hop through a vendor's cloud. The data travels once — from your warehouse to your Mac to its destination.
Check your cloud bill (AWS, GCP, Snowflake) for the 'Data Transfer' or 'Egress' line items. If you see consistent recurring charges that scale with your data tool subscriptions, those are the fees in question. Many teams discover they're paying $500-$5,000/month in egress fees once they go looking.
Yes — even if your Snowflake account and your Salesforce production are both 'in the cloud,' moving data between them through a SaaS vendor's intermediate cloud still triggers egress on the export from Snowflake. QueryFlow's direct path eliminates the intermediate hop.
QueryFlow is a Mac desktop app — not a server-deployed service. For workflows where the orchestrator must live in the same cloud as the data to eliminate all egress, you would need a cloud-native tool. QueryFlow's design is optimized for individual or small-team data engineers working from their Mac.
No. Your warehouse charges for compute (DPU-hours in Redshift, credits in Snowflake) whether the query is initiated from QueryFlow, dataloader.io, or AWS Glue. QueryFlow doesn't reduce warehouse compute costs — it reduces orchestration and egress costs, which are separate line items on your bill.
14-day free trial. Move one egress-heavy pipeline to QueryFlow and watch the AWS bill drop next month.