Analytics execute at the source - data never moves
Traditional data sharing requires copying and moving massive datasets. Zero data movement keeps data secure at the source while still enabling powerful analytics through intelligent query federation.
Zero data movement means analytics execute directly against data at its source. Instead of copying datasets to a central location for processing, queries are federated to where the data lives. Only the computed results move - never the raw data.
Data stays in the source system (data warehouse, database)
Queries execute at the source via secure connections
Only processed results are returned
No data copying, no data lakes, no ETL
Source maintains complete control and security
Security, compliance, and performance benefits
Every data copy is a potential breach point. By keeping data at the source with zero movement, you eliminate duplicate storage vulnerabilities and maintain single-point security controls.
Data movement creates complex regulatory obligations. Zero movement means data never leaves the jurisdiction or control boundaries, dramatically simplifying GDPR, CCPA, and industry compliance.
Copied data is immediately stale. Zero movement means queries execute against current production data, ensuring insights are always accurate and timely.
No data movement means no data lakes, no duplicate storage, no ETL pipelines, no sync jobs. Massive reduction in infrastructure complexity and cost.
Query federation and secure execution
User or application calls the analytics API endpoint with parameters (e.g., 'Get player stats for last 30 days').
The API translates the request into SQL and executes it directly against the provider's data warehouse.
Only the computed analytics are returned to the consumer - raw data never leaves the source system.
No data copies means no additional breach points or attack surface
Data owner maintains complete custody and control at all times
Every query executes against current production data
Eliminate data lakes, ETL pipelines, and duplicate storage
Not with modern architectures. Queries execute on optimized data warehouses with intelligent caching. For most use cases, real-time execution is faster than maintaining synchronized copies.
API SLAs typically include uptime guarantees. Providers can also implement caching layers for high-frequency queries while maintaining zero movement for actual data updates.
Yes - modern analytics APIs can execute complex aggregations, joins, and calculations at the source. For extremely complex ML workflows, you might need raw data, but 80% of use cases work perfectly with zero movement.
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