A problem that every consumer and company faces at some point is the balancing act of operational computing and data analytics. The more advanced the program, the more power needed for back-end operations, which then creates a need for better data analytics. Luckily, Splice Machine exists to help ease and in some cases alleviate the stress of workload overflow.

Monte Zweben, cofounder and CEO of Splice Machine, Inc., talked with John Walls and George Gilbert (@ggilbert41), cohosts of theCUBE, from the SiliconANGLE Media team, during the Spark Summit 2016 about Splice Machine and juggling workloads.

Splicing it together

With an increasing complexity in programming comes a huge increase in data that must be processed. There is the operational data that runs the back-end functions of a program and the data those functions render, which must be analyzed. The problem lies in handling these data streams concurrently.

Splice Machine combines the streams using a relational data-based management system in order to process those massive amounts of data in real time. It is a “dual-engine database,” says Zweben.

Who Benefits?

By combining the operational and analytical sides of data processing, Splice Machine gives time and energy back to the consumer. With the idea of easing the process in mind, Splice Machine has also recently moved to an open-source platform. This decision was made with the idea of creating a “vibrant community,” says Zweben. With more eyes on the programming, they are able to solve for bugs much faster and allow for better analyzation of data streams.

Splice Machine’s capability to process such massive mounts of data makes it a valuable player in the data analytics field, and it is also much more cost effective, according to Zweben. It will allow businesses to “scale out and not up.”

Watch the full interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of Spark Summit 2016.

Photo by SiliconANGLE