CrateDB is a highly scalable SQL database designed for real-time analytics on machine data, capable of handling structured and unstructured data with ease.
| Product | Market Share (%) |
|---|---|
| CrateDB | 0.9% |
| PostgreSQL | 14.7% |
| Firebird SQL | 13.3% |
| Other | 71.1% |
CrateDB provides a unique approach to database management by combining SQL accessibility with NoSQL flexibility. It offers horizontal scaling and distributed SQL queries, enabling users to perform time-series data analysis and geospatial queries effectively. Known for its ability to handle large data volumes, CrateDB is ideal for industries that require fast ingestion and querying capabilities. It supports full-text search, making it versatile for applications that demand quick search operations within large datasets. Users appreciate its open-source model and robust performance, though improvements can be made in areas like documentation and integration with other tools.
What are the most important features of CrateDB?In industries like IoT and telecommunications, CrateDB is deployed for real-time monitoring and analysis of sensor data, providing insights that drive decision-making processes. Its applicability in smart city projects also showcases its power in managing vast amounts of real-time data efficiently. The intuitive nature of SQL coupled with robust data handling capabilities makes CrateDB a choice for businesses looking to innovate big data processes without compromising on performance or scalability.
| Author info | Rating | Review Summary |
|---|---|---|
| product owner at a manufacturing company with 10,001+ employees | 3.5 | I used CrateDB to store high-volume gameplay data with great performance and stability, enabling real-time analytics, though its niche nature and limited community support made it harder to find expertise or robust documentation when needed. |
| DevOps Cloud and Data Senior Consultant at a outsourcing company with 51-200 employees | 4.0 | I used CrateDB for ingesting and analyzing large volumes of log data and found it fast, reliable, and easy to scale, though the CLI and documentation could be improved. It significantly reduced processing time for my team. |
