Analyzing data generated within the enterprise -- for example, sales and purchasing data -- can lead to insights that improve operations. But some organizations are struggling to process, store and use their vast amounts of data efficiently. According to an IDC survey commissioned by Seagate, organizations collect only 56% of the data available throughout their lines of business, and out of that 56%, they only use 57%.

Part of the problem is that data-intensive workloads require substantial resources, and that adding the necessary compute and storage infrastructure is often expensive. For companies moving to the cloud specifically, IDG reports that they plan to devote $78 million toward infrastructure this year. Thirty-six percent cited controlling costs as their top challenge.

That's why Uri Beitler launched Pliops, a startup developing what he calls "data processors" for enterprise and cloud data centers. Pliop's processors are engineered to boost the performance of databases and other apps that run on flash memory, saving money in the long run, he claims.

"It became clear that today's data needs are incompatible with yesterday's data center architecture. Massive data growth has collided with legacy compute and storage shortcomings, creating slowdowns in computing, storage bottlenecks and diminishing networking efficiency," Beitler told TechCrunch in an email interview. "While CPU performance is increasing, it's not keeping up, especially where accelerated performance is critical. Adding more infrastructure often proves to be cost prohibitive and hard to manage. As a result, organizations are looking for solutions that free CPUs from computationally intensive storage tasks."

Pliops isn’t the first to market with a processor for data analytics. Nvidia sells the BlueField-3 data processing unit (DPU). Marvell has its Octeon technology. Oracle’s SPARC M7 chip has a data analytics accelerator coprocessor with a specialized set of instructions for data transformation. And in the realm of startups, Blueshift Memory and Speedata are creating hardware that they say can perform analytics tasks significantly faster than standard processors.