Skip to content
Infrastructure

Distributed Database 

A distributed database built for real-time analytics, large-scale ingestion, and fast SQL queries on any data type.

CrateDB is a distributed database designed for real-time analytics, high ingestion speed, and large-scale SQL workloads. It spreads data and compute across multiple nodes to give you fast queries, strong resilience, and horizontal scale as your datasets grow.

With support for relational data, time series, JSON, text, vectors, and geospatial information, CrateDB delivers the flexibility of a multi-model database and the performance of a distributed analytics engine. All through the simplicity of SQL.

 

Distributed database

 

Built for modern data demands

Traditional databases were never designed for the scale of billions of events, streaming data, diverse formats, and real-time decision making.

CrateDB’s distributed architecture breaks through these limits by spreading both data and query execution across multiple nodes. Each node works independently, processing its share of the workload in parallel.

  • Linear scalability: Add nodes to handle more data or queries instantly.
  • High throughput: Ingest millions of events per second with consistent performance.
  • Distributed execution: Queries are automatically parallelized across all nodes for millisecond-level results.
  • Resilient by design: Built-in replication and failover ensure continuous availability.
cr-quote-image

How CrateDB distributes work

  1. Data sharding: Tables are automatically partitioned into shards distributed across nodes.
  2. Replication: Each shard is replicated to multiple nodes to prevent data loss.
  3. Query distribution: The distributed SQL engine sends query tasks to the nodes holding relevant data.
  4. Parallel processing: Each node processes its part locally and returns intermediate results.
  5. Result aggregation: The handler node merges results and returns the final output in milliseconds.
  6. Everything happens automatically: no manual sharding, no complex clustering setup, no downtime.
cr-quote-image

Multi-model and real-time

CrateDB’s distributed engine isn’t limited to relational data. It processes time series, text, JSON, geospatial, and vector data, all in real time.

Whether you’re monitoring sensors, searching documents, or serving AI models, CrateDB delivers the same speed, scale, and simplicity across every data type.

cr-quote-image

Enterprise-grade reliability

  • Automatic failover: Continuous operation, even if nodes fail.
  • Self-healing clusters: Nodes rejoin and resynchronize automatically.
  • Rolling upgrades: Apply maintenance without downtime.
  • Multi-zone deployments: Distribute nodes across regions for resilience.

This high availability makes CrateDB a natural fit for mission-critical analytics, IoT platforms, and AI-driven applications.

cr-quote-image

CrateDB architecture guide

This comprehensive guide covers all the key concepts you need to know about CrateDB's architecture. It will help you gain a deeper understanding of what makes it performant, scalable, flexible and easy to use. Armed with this knowledge, you will be better equipped to make informed decisions about when to leverage CrateDB for your data projects. 

CrateDB-Architecture-Guide-Cover

Additional resources

Want to learn more?

FAQ

A distributed database stores data across multiple nodes rather than a single server. This improves performance, scalability, and availability. CrateDB uses this architecture to run SQL queries in parallel and provide high ingestion performance.

Real-time analytics depends on fast ingestion, low latency queries, and continuous availability. A distributed design enables these workloads to scale efficiently as data volume increases.

CrateDB uses replication and automatic recovery to keep data available even during node failures. The cluster remains operational while nodes join or leave.
Yes. CrateDB stores time series, JSON, text, vector, geospatial, and relational data in one distributed engine with full SQL support.
You can increase capacity by adding nodes. CrateDB automatically redistributes data and workload across the cluster to maintain performance.