Summary
CrateDB’s scalable and versatile database support the large scale of web, mobile and IoT applications with use cases ranging from smart factories and manufacturing, smart cities applications, geospatial tracking, and cybersecurity.
Problem
Parallel advances in data acquisition, AI and machine learning, automation and microtransactions have posed the basis for environments generating at high frequency and in real time massive volume of heterogenous, and at time unstructured, data and metadata. Incumbent data management solutions are struggling to adapt to this new paradigm and face issues due to the increasing scope, scale and velocity of data. On the other hand, new use-cases across industries that require little to no latency and that cannot be addressed with legacy technologies.
Solution
Crate’s core product CrateDB is a SQL database built atop NoSQL storage & indexing for collecting, managing and analyzing machine data in real time. It has the versatility and scalability to handle the variety, velocity and volume of machine data–millions of structured and unstructured data points or log entries per second. Their architecture is completely "masterless" which means there is no single point of failure, can scale in and out simply through addition/deletion of nodes and can run on devices as constrained as a Raspberry PI. CrateDB also provides the unique ability to distribute queries across nodes.
Crate.io also released MDP, a Kubernetes container environment, which secures and scales CrateDB in the cloud (or on-premises), along with customer data loading, data enrichment, analytics, visualization and alerting code. Its use cases include smart factories and manufacturing, smart cities applications, geospatial tracking, and cybersecurity. CrateDB has been designed from the ground up to support the huge scale of web, mobile and IoT applications and is increasingly affirming itself as a category leader.
