NoSQL on HPC – (SQL Queries/Tables, OLTP transactions): See How Gensonix is the “ALL BIG DATA” Solution

A challenge we face every day: SQL DBs handle structured data while NoSQL DB’s handle unstructured data. This has forced most customers to deploy 2 DB’s. To avoid this overhead, it has also been found that many enterprises are utilizing SQL DB’s to store unstructured data as well as NoSQL DBs to store structured data. This cross migration puts a toll not only on cost, but on efficiency as well as humongous system sizing.

Gensonix® NoSQL DB is ‘THE’ viable solution; its structured data capabilities supporting relational type tables and queries provide support for OLTP as well. Gensonix promotes multi modeling with schema-based relational tables for true structured data with add on Network and Column models to eliminate costly and repetitive indexing. This improves performance while saving tremendously on storage requirements. Additionally, Gensonix supports schema less key value/document type stores for all forms of unstructured data thereby improving efficiency.

Gensonix can run on industry standard hardware; however Gensonix Enterprise NoSQL DB is optimized for HPC systems such as the Scientel® LDWA. On HPC, Gensonix renders the most efficient MPP architecture for delivering massively parallel processing. Gensonix true MPP architecture allows full utilization of entire CPU core fleet to effectively process equal parts of the DB providing high efficiency and performance. Finally, the flexibility and efficiency of the NSQL™ language when combined with the efficient MPP architecture delivers performance that matches other in-memory systems without the cost of in-memory implementations.

Gary Heitman began his IT career with Uniroyal Tire Company where he evolved from operating large Mainframes to developing new dealership and in-house applications in VB & Fortran. When Uniroyal relocated, he joined Ford Motor Company. He progressed from COBOL and C++ programmer to Analyst; ultimately Global IT Project Manager. He developed a system for determining the most profitable assembly plants worldwide to build vehicles. His work with reducing vehicle complexity was recognized as game-changing. He became an IT consultant and uses data analytics to support corporate decision-making. Gary continued sharing his technical knowledge and business background when he joined Scientel. His vision is that organizations will be able to collect and use every byte of relevant Big Data to make the best decisions possible. Gary holds a B.A. in Organizational Psychology from University of Michigan-Dearborn, and he is passionate about engaging with people and the power of social networking.