International Business Machines Corporation
Cognitive compression with varying structural granularities in NoSQL databases

Abstract:

Cognitive compression with varying structural granularities in a NoSQL database by establishing a data training set for compressing and decompressing data stored within the NoSQL database. The data training set includes received user policy goals, compression parameters, and metered feedback associated with data usage and workload characteristics. A compression parameter model is dynamically implemented in real-time for the data selected according to the established data training set to compress and decompress the data at a given structural granularity.