24
Sep

CEO Blog: Why we are introducing Infopliance

Money.

Yours, not ours. Well, that's not entirely true, yours and ours. We believe if we can help organizations save a ton of money, then we can make a lot along the way. Everybody wins. Or almost everybody. When organizations choose to bring in an Infopliance, they will be doing that in lieu of an alternative. So let's explore that. Why the Infopliance?

Over the past two years, anyone who has followed Infobright has surely noticed our focus on machine-generated data. This is because our software has some unique advantages when this is the type of data being stored. This is normally associated with weblog analysis and online or mobile analytics, the storage and analysis of call data records, applications involving storage and analysis of sensor data like smart grid technology, and the the storage analysis of network events, IT logs, and other related use cases. Our customers include a strong growing list of AdTech players like Yahoo!, AdSafe Media, LiveRail, Bango, and many others. They are solution providers to the telco and network analytics space like JDSU, Mavenir, Polystar, IMImobile, Sonus Networks as well as others in the security space like SonicWALL, now a part of Dell. Our website has case study after case study, and our YouTube channel has a number of excellent videos showcasing these success stories. And the reason our joint efforts with our users are successful is simple: we provide a platform for storing and analyzing machine-generated data that delivers great performance, especially when you need to be able to do ad hoc queries and data mining, with superior disk compression and virtually stripping out the database administrator requirements. So in the end, we deliver great results for an exceptionally low total cost of ownership. It is inexpensive and easy and quick to get up and running and stay up and running.

In the last year, many of our customers have had explosive data growth, and we have been brought into a number of new opportunities that have a starting point of much greater volumes of data. While the average starting point in the past has been 1TB - 2TB of data, we are seeing more and more starting at anywhere from 10TB to 50TB. And in these instances we are seeing that a natural consideration is to look to general purpose database appliances like a Teradata, Netezza, or Oracle Exadata. These are great solutions. They all have their pros and cons. All products do. I have a healthy respect for these companies and their solutions.  They are designed to provide an easy-to-establish and maintain enterprise data warehouse or even a mixed workload, more comprehensive environment. That is not our thing at all. We focus on machine-generated data. So the more extensive platform does way more. But herein lies the driver as to why we are introducing Infopliance: many people are buying general purpose data warehouse appliances and storing machine-generated data, and just machine-generated data, on those machines. It works, but it's a very, very expensive path. Everyone who has done this admits it freely. This is not like a state secret. So we saw a gap in the market, where as more and more organizations are storing larger amounts of this type of data, we could offer the industry's first purpose-built machine-generated data appliance, which would cost significantly less than the more general purpose alternatives.

And the icing on the cake is that while Infopliance acquisition costs are lower, and the operational costs are lower as well, there are additional unique capabilities that you would not get on a general purpose appliance. Capabilities like utilization of our Knowledge Grid, where everything is tantamount to being indexed, although no indexing or other DBA work is required. Capabilities like DomainExpert, allowing you to exploit the patterns in the data to more efficiently leverage the Knowledge Grid for even greater performance and compression. And capabilities like Rough Query, providing innovative investigative analytics techniques that allow for blindingly fast interrogation of huge datasets in order to better narrow your scope, much like a detective would do in a crime investigation. The way data is interrogated must change as the realities of Big Data sink in. And they will. But still, at the forefront in many minds is the need to store and analyze much more data without spending millions and millions. And that is the primary capability we can deliver with Infopliance.

We believe the machine-generated data market, and more broadly, the proliferation of mobile devices, and the explosion of a Machine to Machine (M2M) world will reveal overwhelming demand for this type of offering. And while we expect there will be other companies to follow in time with their own purpose-built appliances for machine-generated data, we are proud to get here first; we are especially proud of our patented technology that underpins this offering; and we are most proud of the strong customer and partner base that has validated our approach more and more over the last few years.

Regards,

Don

The first paragraph of http://www.marketwatch.com/story/infobright-unveils-first-database-appliance-purpose-built-for-analyzing-machine-generated-data-2012-09-24 says, “The Infopliance(TM) system scales from 12 to 144 terabytes of data in a single appliance node and costs under $4,900 per terabyte of data at the high end….”

Does an Infopliance(TM) system for 144 terabytes of uncompressed data cost less than $705,600 ($4,900 multiplied by 144)?

Author: Alan Musnikow
Date: 10/07/12

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