Real-time flexibility
CrateDB eliminates the trade-off between performance and freshness. You can query hot data as it’s ingested, from IoT sensors, logs, or user events, without replication or delay.
Key advantages:
- Query live and historical data in the same statement
- Execute joins, filters, and aggregations across billions of records
- Get instant results, even as new data flows in
Native SQL, no learning curve
CrateDB speaks SQL natively, making it instantly familiar to developers, analysts, and data scientists. You can query structured, semi-structured, and unstructured data in the same language, with full support for JSON, geospatial, time-series, and vector data.
Example use cases:
- Investigate anomalies in streaming telemetry
- Run ad-hoc reports on IoT or application events
- Explore patterns and correlations across multiple data types
Automatic indexing and optimization
CrateDB automatically indexes every column and field, ensuring high-speed lookups and aggregations without manual tuning. Its distributed planner dynamically optimizes query execution, leveraging parallel processing across all nodes.
Why it matters:
- Zero manual index management
- Consistent performance under heavy load
- Sub-second response time on large datasets
Native SQL, no learning curve
CrateDB speaks SQL natively, making it instantly familiar to developers, analysts, and data scientists. You can query structured, semi-structured, and unstructured data in the same language, with full support for JSON, geospatial, time-series, and vector data.
Example use cases:
- Investigate anomalies in streaming telemetry
- Run ad-hoc reports on IoT or application events
- Explore patterns and correlations across multiple data types
Instant insight for everyone
Because CrateDB uses SQL and integrates with BI and visualization tools, anyone can ask questions and get answers, from developers and data engineers to business analysts.
Integrations include:
- Grafana and Tableau for dashboards
- Jupyter and Python for exploration
- JDBC/ODBC for custom analytics pipelines
Ad-hoc queries in action
Imagine a logistics platform tracking millions of shipments per hour. With CrateDB, you can query delivery delays, identify bottlenecks, and filter by region or carrier, in real time, as data is being ingested. No ETL. No waiting. Just answers.
Why choose CrateDB for ad-hoc analytics
| Traditional databases | CrateDB’s real-time approach |
|---|---|
| Require pre-aggregated tables or views | Query raw data instantly |
| Performance drops with large datasets | Distributed parallel execution |
| Schema updates cause downtime | Dynamic schema, no disruption |
