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What in-memory computing can do for you (and your Big Data)

Unlike traditional Big Data analytics methods that separate data storage from the processing elements, in-memory computing uses main memory for storing data.Using simplified algorithms, in-memory computing executes fewer CPU instructions and reduces seek-time during the data-query process, resulting in much faster performance than disk-based data storage. As a result, what once took hours or minutes to process can now take minutes to seconds. 

 

 

Many of you are looking at in-memory computing as a way to handle your Big Data needs and challenges. An article in the August 2014 issue of Technology@Work talks about the benefits of in-memory computing that you can read in full here. Frances Guida, manager of Converged Systems Messaging and Content at HP, was interviewed for the article and says this:

 

“There are two aspects that in-memory computing can address. Businesses have a lot of data that gets distributed in many different databases across many different disks—and they have a hard time making use of all that information the way it’s distributed around the organization.”

 

“In-memory computing allows enterprises to make better use of that information,” she says, as users “can analyze massive data sets much more quickly and with much more ease. You can put the power of all that data together and handle it in a real-time fashion—for example, performing business analytics on your production data without impacting your ability to process transactions.”

 

The second part of the equation is the speed that IMC imparts on analysis and Big Data sets. “By having everything in-memory, by definition, you’re always getting the speed that allows you to do things like take transaction times that might have taken minutes, and move them to seconds,” Guida says. “Queries and analytical workloads that could take hours can be reduced to seconds, because you don’t have to go out to that slow disk and can access the data straight out of the memory.”

 

SAP HANA is an in-memory computing technology.

In-memory technologies like SAP HANA provide a common platform designed for faster big data analytics, a more scalable data warehouse and ability to migrate all business applications to one underlying data base. Since the launch of SAP HANA, HP has been at the forefront of innovating leading benchmarks and solutions. Through its HP Center for Excellence for in-memory computing, SAP and HP are bringing new products and technologies to market, integrating transactional and analytics systems, so customers can run their businesses in real time.

 

The HP ConvergedSystem for SAP HANA is a portfolio of pre-integrated systems optimized for in-memory computing with the highest levels of performance and availability, unmatched scalability and the fastest time-to-value. The systems integrate the server, storage, networking, software and services that clients need to power their SAP HANA environment in all-in-one systems that are quick and easy to deploy, managed as one, and have integrated services to ensure optimal performance today and into the future. 

 

Guida cites a customer who is using one of HP’s SAP HANA solutions.

 

“We have companies that have taken those classic MRP processes that used to take hours and get that down to minutes or seconds,” Guida says. “For example, India’s largest bicycle manufacturer used to take one and half to two hours to run their MRP reports. They had to do them overnight because the system didn’t enable them to run during the day. Now it takes only 10 to 15 minutes, and they can run reports several times per day.”

 

 

Read the Technology@Work article and consider what in-memory computing can do for you.

 

Celia

 

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Technology marketing professional with over 25 years of experience in energy, semiconductor and IT industries.


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