Kognitio has been named as one of the top companies working in the big data sector by one of the technology industry's leading publications.

CRN has published its inaugural Big Data Business Analytics Top 100, which identifies the firms that have shown a proven ability to innovate in the big data analytics sector and bring to market products and services that help companies make the most of their business intelligence information.

The publication noted many enterprises are struggling with the volume, speed and variety of data they are generating on a daily basis. This development – known as big data – has been identified by organizations such as Gartner as being one of the defining forces that will drive business IT investments in the coming years.

CRN said: “Companies are seeking technologies that not only help them process and manage all that data, but tap into it to develop insights about the markets they compete in as well as their own performance within those markets.”

This is why it has published the Big Data Business Analytics Top 100, which may assist businesses when it comes to choosing their partners in the sector. 

Kognitio was among the companies named on the list, with CRN particularly highlighting its analytical platform, which is the industry's first solution that leverages in-memory computing to help companies with analyzing large data sets.

This platform can run either as an on-premises solutions or in a private or public cloud as a Platform-as-a-Service. The fact it is also compatible with most ETL and business intelligence tools available today was also highlighted by CRN.

However, this is not the only praise Kognitio has won recently. Its solutions also came out favorably in an evaluation of in-memory analytics solutions conducted by Enterprise Management Associates.

This study compared Kognitio's offering to SAP HANA and Oracle TimesTen and it was described as “the most mature platform” of the three. It was also praised for the fact it uses row-based data loading over more complex traditional columnar approaches.