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Query Performance

CrateDB provides high-performance capabilities with query response time in milliseconds to process and analyze data efficiently. With its advanced capabilities, CrateDB provides a high-performance distributed query engine, writes, and reads, enhancing query performance significantly:

  • Distributed Query Engine: CrateDB’s query engine is architected to optimize data throughput and query performance, particularly as the number of concurrent operations grows. Key features like distributed query processing, advanced indexing techniques, real-time data ingestion, and real-time querying, synergize to deliver a seamless and high-performance user experience.
  • Distributed Writes: CrateDB employs a sharding mechanism to distribute data across multiple nodes in a cluster. This sharding strategy enables parallel write operations, allowing independent and concurrent writing to each shard on different nodes. This distribution prevents any single node from becoming a bottleneck, improving write throughput and scalability.
  • Distributed Reads: CrateDB’s design, focused on distribution, leads to operations being split across shards and their replicas by the query planner. This strategy accelerates aggregations by selecting only the necessary data partitions, utilizing available hardware on individual nodes, distributing queries across all nodes, and pushing down aggregations to multiple nodes to reduce pressure during the merge step of query execution.

CrateDB's fully distributed query engine and columnar storage bring the following benefits: 


1M inserts per second with a CrateDB cluster of 5 standard nodes only

Learn more about the latest benchmark on CrateDB performance >

ABB Ability™ Genix optimizes operations and increases asset availability in industrial use cases by analyzing vast amounts of data in real-time. They use CrateDB to unlock the value of industrial data, working with advanced data analysis and data management capabilities. With a data ingestion rate of an 1 million values per second and event retrieval ranging from 30,000 to 120,000 events per second, ABB optimizes industrial efficiency and productivity.

"Working with CrateDB brings positive outcomes. The ingestion and throughput have very good performance, with 1 million values/sec, the horizontal scalability where we can add as many nodes as we need and the automatic query distribution across the whole cluster"

Marko Sommarberg
Lead, Digital Strategy and Business Development at ABB


With CrateDB, ABB could achieve:

1 Mill values/sec 30k to 120k event/sec
Data ingestion Event retrieval

Additional resources

CrateDB at Berlin Buzzwords 2023

When ms matter: Maximizing query performance in CrateDB

On-demand workshop

Query Planning and Optimizations

Customer interview

Redefining warehouse intelligence with CrateDB

"Our distribution centers produce a lot of sensor data and we enable our customers to take data driven decisions. CrateDB allows us to operate on any Cloud and on-prem/Edge with simplicity and stellar performance, and significant cost advantages."

Alexander Mann
Owner Connected Warehouse Architecture
TGW Logistics Group

Community Day Talk

Make use of CrateDB's performance potential

how can you scale efficiently with CrateDB and achieve performant queries? You will learn how sharding & partitioning choices, along with correct data modeling can get you there. Also, discover how to monitor your cluster to avoid unpleasant surprises, as Marios shares his best practices to keep your cluster healthy at all times! Finally, you'll learn about the key factors which will allow you to deploy CrateDB to the cloud and achieve the desired performance. 

Community Tutorial

Optimizing storage for historic time-series data

When dealing with time-series data, performance is crucial. Data that gets ingested should be available quickly for querying. To enable fast decision-making, analytical queries often need to return results in a fraction of a second.


Join performance to the rescue

Improve query performance in CrateDB by fine-tuning the query optimizer. Learn how to fixate the join order and enhance execution time. Find out more!


How we scaled ingestion to one million rows per second

One of CrateDB’s key strengths is scalability. With a truly distributed architecture, CrateDB serves high ingest loads while maintaining sub-second reading performance in many scenarios. In this article, we want to explore the process of scaling ingestion throughput. While scaling, one can meet a number of challenges - which is why we set ourselves the goal of scaling to an ingest throughput of 1,000,000 rows/s.


Load testing CrateDB using Locust

Learn to assess and enhance the performance of your CrateDB environment using the Locust framework in this tutorial. 

Want to learn more?