One of the questions we regularly get asked at Exasol is how well our in-memory analytic database scales.
Does our analytic database perform just as well on petabytes of data as it does on small data volumes?
The answer, of course, is yes, but it is always fun to hear how excited our customers get about the prospect of building large database instances, environments where they can analyze billions and trillions of rows of data in just seconds. It would appear that many of our customers envisage running their analytics on lots of servers in a huge cluster farm so that they can get answers to their questions fast and take their businesses to new levels. Size matters, right?
Well, not everyone may want to run an analytic database across a server farm or even a small cluster; their need may be quite different and much smaller. So, how do you help those that want to test an analytic database but don’t want to invest in hardware? While Exasol of course can be implemented in cloud-based architectures (AWS, Azure, Bigstep, ExaCloud, Rackspace etc.) which have their own advantages, we’re glad to announce a different solution, which we call “Exasol in my pocket.”
The approach is simple. Take a small computing device that fits into the palm of your hand such as Intel’s four-inch square NUC server device, load a free copy of Exasol onto it and perhaps also Tableau, and off you go. In fact, kudos goes to our partner, Atheon Analytics, and its chief data animator, Guy Cuthbert, who came up with the idea. While talking to organizations about Exasol, Guy saw the need to use a small device that could run Exasol to get over the limitations of network bandwidth or running the database on a laptop, especially when it came to loading data. By bringing Exasol on a NUC in such a compact package, Guy and his team are able to run a far more efficient and accurate proof-of-concept for their customers without relying on the customers’ internet connection.
Indeed, now scalability works two ways, both up and down, by using Exasol to query millions of rows in real-time but on a device in the palm of the hand. So, while many may continue to focus on large-scale implementations and get excited about size, it’s refreshing to see how users can also get started with Exasol today using a device that performs just as well on smaller data volumes, and, more conveniently, fits into your pocket.
Size matters? Maybe. But it’s performance that counts.