Authentic multidimensional data model based on cubes and dimensions.
All cubes do not exist in isolation, they can be jointly queried to provide in-depth data analysis capabilities.
EuclidOLAP can provide real-time aggregate computing capabilities for data of any granularity without prior pre-aggregation calculations.
Support for MDX(Multi-Dimensional Expressions), which can better describe multidimensional models and perform multidimensional queries than SQL.
EuclidOLAP's powerful instantaneous query capabilities enable data analysts to quickly implement their ideas without having to create indexes or precompute, enabling exploratory data analysis.
EuclidOLAP uses the SIMD features of the CPU to improve computing performance, and EuclidOLAP computing nodes running on GPU processors can provide tens to hundreds of times higher computing performance than CPUs.
You can deploy an EuclidOLAP service instance in just a few minutes on the Linux operating system, or use a Docker command to run an EuclidOLAP container.
EuclidOLAP can either run in stand-alone mode or be deployed as a horizontally scalable distributed architecture.
The EuclidOLAP solution deployed in cloud environment uses nearly unlimited elastic computing resources in the cloud to maximize the data mining potential of EuclidOLAP.