Space-Time Insight joined CrateDB in their launch of CrateDB 1.0, an open source SQL database that enables real-time analytics for machine data applications. We make extensive use of machine learning and streaming analytics, and CrateDB is particularly well-suited for the geospatial and temporal data we work with, including support for distributed joins. It allows us to write and query sensor data at more than 200,000 rows per second, and query terabytes of data. Typical relational databases can’t handle anywhere near the rate of ingestion that Crate can.
Crate handles and queries geospatial and temporal data particularly well. We also get image (BLOB) and text support, which is important for our IoT solutions, as they are often used to capture images on mobile devices in the field and provide two-way communication between people and machines. Crate is also microservice-ready — we’ve Dockerized our IoT cloud service, for example.
Finally, our SI Studio platform uses Java and SQL and expects an SQL interface, so choosing Crate made integration straightforward and allowed us to leverage existing internal skill sets.