Automatic indexing on ingest
CrateDB continuously indexes incoming data in real time. There’s no need for manual index creation or reconfiguration. Every column and nested field is automatically indexed and optimized for fast search and aggregation.
Key benefits:
- Instant data availability after ingestion
- No manual index management
- Consistent performance under heavy write loads
Parallel and distributed indexing
Indexing happens in parallel across all nodes and shards in the cluster. This distributed approach ensures that ingestion and indexing scale together, maintaining low latency even as data volumes grow exponentially.
Why it matters:
- Index millions of new records per second
- No single-node bottlenecks
- Always up-to-date indexes for real-time visibility
Search and query instantly
Once data is indexed, it’s immediately accessible for SQL queries, full-text search, vector similarity, and aggregations, all from a single engine. This unified approach removes the need for external search systems, data duplication, or sync delays.
Use cases:
- Real-time monitoring and anomaly detection
- Log and event analytics
- AI-driven applications relying on live signals
Always fresh, always fast
CrateDB ensures that your indexes evolve as your data evolves, without downtime.
Whether you’re adding new columns, changing schemas, or scaling clusters, indexing continues uninterrupted so you always have the latest view of your data.
Highlights:
- Dynamic schema updates with zero disruption
- Consistent query performance on fresh data
- Real-time observability across all sources
Why choose CrateDB for real-time indexing
| Traditional databases | CrateDB’s real-time indexing |
|---|---|
| Manual index management required | Automatic, parallel indexing |
| Delayed availability after ingestion | Queryable within seconds |
| Separate systems for storage and search | Unified analytics and search engine |
