Compare CrateDB

How is CrateDB different from other databases in the market?

There is no one-size-fits-all when it comes to databases: the ideal database will be determined by your use case and dataset. The characteristics of CrateDB make it optimal for real-time IoT use-cases with high data volumes, data variety, and heavy load, as it is the case, for example, in industrial IoT.

Industrial IoT use-case


Icon "High Data volume"
High data volume
Icon "Unlimited Scalability"
Unlimited scalability
Icon "Different types of data"
Different types of data
Icon "Versatile data model"
Versatile data model
Icon "Concurrent users"
Concurrent users
Icon "High concurrency performance"
High concurrency performance
Icon "Real-time response"
Real-time response
Icon "Dynamic architecture"
Dynamic architecture
Icon "Frequent changes"
Frequent changes
Icon "Easy integration"
Easy integration
Icon "Efficiency as priority"
Efficiency as priority
Icon "Cost efficiency"
Cost efficiency
Icon "Need for versatility"
Need for versatility
Icon "Run any cloud, EDGE and on premises"
Run in any cloud, EDGE and on premises

CrateDB is neither a relational database, nor a NoSQL database, nor a time-series database; instead, it offers the best of these worlds. CrateDB is a distributed database built on a NoSQL foundation, but fully accessible through SQL.

CrateDB is able to work with large datasets without losing accuracy, keeping things simple and efficient. And due to its real-time features, indexing, and schemas, CrateDB is ideal for handling huge amounts of time-series data.

  Traditional RDBMS NoSQL Time-series databases CrateDB
High data ingestion - Checkmark Icon Checkmark Icon Checkmark Icon
High data versatility - Checkmark Icon - Checkmark Icon
Real-time performance - - Checkmark Icon Checkmark Icon
Simple scalability - Checkmark Icon - Checkmark Icon
SQL access Checkmark Icon - - Checkmark Icon

CrateDB VS Traditional RDBMS

Traditional relational databases can be an excellent choice for a use case without huge data volumes or high scalability needs. But they are insufficient for IoT applications demanding horizontal scalability and the real-time processing of massive datasets.

Traditional RDBMS CrateDB
Accessibility ANSI SQL ANSI SQL
Core architecture Monolithic or master/slave Shared-nothing nodes
Data model Rigid schemas of tabular data Dynamic schema, structured & unstructured data
Consistency model ACID Eventually consistent
Scalability model Vertical scaling Horizontal scalability
Partitioning Manual Built-in
Full-text search Not built-in Built-in (Lucene indexing)
Microservices architecture Compatible Ideal
White Paper

CrateDB vs PostgreSQL

In a benchmark querying 312 million rows of sensor readings, CrateDB provided 33x better price-performance than PostgreSQL.

CrateDB vs NoSQL

NoSQL databases like MongoDB are not the best choice if you are dealing with huge volumes of time-series data that need to be queried in real-time. NoSQL databases can get very expensive for IoT use cases at scale, consuming unnecessarily large memory and storage capacity. At the same time, you must abandon the power and convenience of SQL.


Comparing databases for an Industrial IoT use-case

In this blogpost we talk about our experience as developers working with MongoDB, TimescaleDB and InfluxDB, discussing the pros and cons of every database for large-scale IoT.

CrateDB vs time-series databases

Time series databases like InfluxDB or TimescaleDB are unable to handle many IoT applications by themselves—if they require metadata operations, for example. They often need to work in combination with an RDBMS, duplicating maintenance efforts and costs. Besides, their performance is usually optimized for single-node processes.

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Comparing Databases
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The cost of running MongoDB, TimescaleDB and CrateDB for industrial IoT

Find out how much the monthly price can vary if different databases are used

Try CrateDB Cloud

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See what our engineers are up to. We welcome contributions, feedback and discussions.

Download CrateDB

CrateDB is the leading open-source, distributed SQL database for relational and time-series data. Download it for free.