crate open source analysis

CrateDB is a distributed and scalable SQL database for storing and analyzing massive amounts of data in near real-time, even with complex queries. It is PostgreSQL-compatible, and based on Lucene.

Project overview

⭐ 4348 · Java · Last activity on GitHub: 2026-01-05

GitHub: https://github.com/crate/crate

Why it matters for engineering teams

CrateDB addresses the challenge of managing and analysing large volumes of time-series and IoT data in near real-time, which is essential for engineering teams working with complex datasets. It offers a distributed and scalable SQL database that is PostgreSQL-compatible, making it accessible for teams familiar with SQL while handling big data workloads efficiently. This open source tool for engineering teams is particularly suited to machine learning and AI engineering roles that require fast data ingestion and advanced analytics. CrateDB has matured into a production ready solution with proven reliability in industrial IoT and analytics environments. However, it may not be the best fit for projects that require a lightweight or purely transactional database, as its strength lies in distributed, analytical workloads rather than OLTP scenarios.

When to use this project

CrateDB is a strong choice when your team needs a self hosted option for scalable, real-time analytics on large datasets, especially with time-series or IoT data. Teams should consider alternatives if their primary focus is on simple transactional databases or if they require extensive customisation beyond PostgreSQL compatibility.

Team fit and typical use cases

Machine learning and AI engineers benefit most from CrateDB, using it to store and query vast amounts of sensor or event data for model training and real-time inference. Data engineers also use it to build analytics pipelines in products involving industrial IoT, monitoring, and time-series analysis. Its role in these teams is to provide a reliable, scalable backend that supports complex SQL queries on distributed data.

Best suited for

Topics and ecosystem

analytics big-data cratedb database dbms distributed distributed-database distributed-sql-database elasticsearch industrial-iot iot iot-analytics iot-database lucene olap postgresql sql time-series tsdb vector-database

Activity and freshness

Latest commit on GitHub: 2026-01-05. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.