In-memory big data processing may provide the solution to enterprises seeking faster data insights.
Fast isn't fast enough for some enterprises looking to recoup big data insights. After all, not every big data query can wait until the next day--or longer. Organizations want business insights in real time or near real time. One way they are getting there is by implementing in-memory data processing, which can return almost immediate results.
"We have seen in-memory big data processing explode over the last two years," said Matthias Golombeck, CTO at Exasol, an in-memory big data processing provider.
In fact, to meet the growing demand for in-memory processing legacy system companies such as Oracle, IBM, Microsoft, and Teradata have added in-memory big data processing capability to their databases.
"The goal is to use the compute power of your hardware to process more complex algorithms and data faster so you can provide faster access to results," said Golombeck.
Is in-memory big data processing right for your company?
Is in-memory big data processing something your company should consider? Here are four examples where in-memory big data processing is a must-have.
1. Your organization is a real-time business where any time lost can impact revenue and customers
Online retailers represent a good example of this. If they can't anticipate their customers' needs instantaneously, or perform instantaneous order fulfillment, they could lose both revenue and customers.
2. You have to stay up with the competition
No matter what industry you're in--if your competition uses real-time analytics with big data, and it gives them a competitive edge, you need to get in the game, too.
3. You depend on IoT
Manufacturers, facility management firms, gas and power companies, warehouses, logistics companies, grocery stores and other industries that depend on IoT, such as sensors, need system alerts in real time. Otherwise they are introducing personnel, security and production risks.
4. You deliver a real-time product or service
Cable or communications business, which provides live media broadcasts, need to deliver big data in real time. In-memory processing can facilitate this.
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