UPDATED 09:01 EDT / MAY 22 2015

NEWS

Why is this Ashton Kutcher-backed SQL startup taking a shot at geospatial data?

MemSQL Inc., which is probably the only high-profile database startup that can boast of an active A-lister among its investors, has pulled the curtains back on a new version of its namesake in-memory store that is hailed as the most significant iteration yet. The addition earning the release that lofty designation is the ability to natively accommodate location data.

That allows organizations to keep the growing amounts of information entering the corporate network from the connected universe, which almost universally incorporates positioning metrics one way or another, in the same system as their more conventional relational workloads. This has two major benefits, according to the startup, first and foremost streamlining operations.

The ability to consolidates all those different datasets into a single environment not only eliminates the need to pay for additional systems but also the manual overhead associated with managing them, which further reduces expenses while freeing up administrators for more productive tasks. That includes analyzing the information, which is where the second benefit of the new release comes in.

Having everything in the same environment makes the data more accessible in use cases that include combining multiple types of input. which are becoming increasingly common in the enterprise and particularly especially among MemSQL’s tech-oriented customers. The list includes the likes of Zynga Inc. and Verisign, Inc. as well as (very likely) the intelligence community, which bought into its technology as part of a funding round last year with the goal of exploring adoption opportunities.

Those organizations will able to put their geospatial data to use through new integration with Apache Spark also introduced in the update that promises to make it much easier for administrators to move their workloads into the speedy execution engine for analysis. MemSQL envisions its database being used to store frequently-used information that necessities faster access speeds than what the disk-oriented Hadoop File System can provide.
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