Real-time raw-data analytics¶

CrateDB provides real-time analytics on raw data stored for the long term.

CrateDB eliminates the trade-off between data accessibility and storage costs by keeping all high-volume raw data in the hot zone without requiring downsampling or aggregation. Unlike traditional systems that force you to choose between real-time query capabilities and long-term retention, CrateDB handles billions of records while maintaining fast query performance on the full dataset.

Traditional analytics pipelines rely on pre-aggregated rollups or batch processing to handle query loads, limiting users to predefined metrics and losing the granularity needed for ad-hoc analysis. CrateDB’s distributed architecture scales horizontally to support exploratory queries on complete raw datasets in near real time, enabling analysts to discover insights that would be invisible in downsampled data.

By keeping all records immediately available for querying, you avoid the complexity of maintaining separate hot and cold storage tiers, ETL pipelines for aggregation, or data movement processes. Your analytics queries run directly on raw data across any time range, delivering the accuracy and flexibility that business intelligence and data science teams require.

With CrateDB, compatible to PostgreSQL, you can do all of that using plain SQL. Other than integrating well with commodity systems using standard database access interfaces like ODBC or JDBC, it provides a proprietary HTTP interface on top.