/ Keeping up with Big Data’s Growth Curve

SAP recently unveiled their Hana offering which is an exciting new data storage technology and started another chapter in the big data, high performance computing saga — a sector now getting lots of attention from the BI industry. And rightly so as the industry struggles to deal with the exponential increase in data growth .

It is a race that the BI industry has spent the last 15 years trying to win by inventing and re-inventing solutions to keep up with the data growth curve. And, after all that effort, they are still behind. I do think that the idea of federating commodity hardware into MPP grids has the good chance to yet catch the ever expanding data growth curve. Especially, when coupled with the innovation going on the area of big data no SQL databases. It is a welcome development indeed to have viable choices beyond the traditional SQL databases — and just in time too. The Mongo DB, H-base, Cassandra and other offerings in the no SQL databases genre are bringing tremendous new alternatives to the space. In my opinion this technology shows great promise in providing a cost effective basis to keep up with the ever-increasing data explosion.

It’s all very exciting especially to the folks who consider winning being able to handle a multi-pedabyte database and have a request return in the same day. But for us at Domo winning isn’t defined as building a bigger, faster data box. Where it gets interesting for us is when the data is out of the box and making meaningful impact on executive management decisions. In the commercial sector, we consider winning as increasing the revenue, market share and wallet share of our customers. So to the data box builders and big data no SQL database providers, keep on chasing that growth curve and we hope you catch it…In fact, we are counting on it so we can leverage the technology to help our customers win in the Domo way.

So, what do you think? Do you agree that the combination of both the MPP Grid Computing and no SQL database technologies provides a cost effective foundation for keeping up with the data growth curve or is yet another innovation needed?

Tags: big data, data

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