The main purpose of this service is analyzing a huge amount of structured data. This data processing service can produce various of the aggregated results based on pre-configured methods and criterias to get useful and understandable reports. Such service is accessible for a user through the interface as well as API access to the aggregated results that had already been computed. (Shorter: (M)OLAP Technology)

The main advantages of this approach are:

Data amount

virtually unlimited amount of input data

Response time

short and predictable request response time for the computed results. It doesn't depend on neither the volume of data nor complexity and type of the used aggregation functions

Aggregation

any complicity of aggregation functions

Price

relatively cheap CPU resources due to the Hadoop framework

Possible use cases:

formatted raw data analysis (i.e.: log files)

processing data from any kind of telemetry sensors (weather, GPS positioning, health and sport's tracking, etc.)

The product can be delivered as

SaaS solution based on shared Hadoop cluster/cloud

Based on the client’s dedicated private cluster/cloud

"Boxed version" of a single-host setup for the clients with the existing Hadoop infrastructure

As-is freeware

Currently, the project is in an alpha version and is expected to be released as beta before the end of the year for the closed testing.