In-memory technology: Serving up application data to users on the go

Data can be viewed to be as valuable in the digital business world as oil is to the economy. Oil fuels homes, cars, railroads, and even electricity. Data powers the business and revenue. Businesses that want to continue to evolve, transform and improve need are being fueled by their data to tell them where and when to make changes.

It’s not just about obtaining data though. Businesses that want to remain competitive need to gain intelligent and valuable insights fast and in real-time. Yesterday’s data will be worthless tomorrow when every second to deliver high-quality experiences matters today. If a service is slow, if a system goes down, or if a customer can’t find what they are looking for, they won’t waste too much time with your business before moving on.

The challenge, however, is that there is an influx of data coming in from every direction, and that is making it difficult to collect, store, and manage data. The traditional approach to storing data is to put it on a disk-based system for later integration and analysis. In addition to being slow and not conducive to today’s fast-paced way of working, disk requires a lot of overhead involved with querying, finding and accessing data.

“Customer expectations around latency and responsiveness have skyrocketed; today everyone expects constant availability but latency is now considered the new downtime. In other words, brownout is the new blackout in today’s world. In order for businesses to meet and exceed these customer expectations, businesses and IT leaders can no longer rely on old traditional ways of storing and managing data,” said Madhukar Kumar, vice president of product marketing for database provider Redis Labs.

The alternative approach is to store data in memory, but that has not been an option to many businesses because of the cost expense compared to disk until just recently. Recent advances in the memory space are making storing data in memory and in-memory databases more cost effective, according to Mat Keep, senior director of products and solutions for the database platform provider MongoDB.Keep explained that over the last couple of years, memory technology has improved with capacity going up and costs going down. “We are seeing real growth and commoditization of in-memory technology,” he said.

This gives you a competitive advantage because with in-memory computing, businesses can feed their compute capability at a much higher rate and get a much faster access path to data, Keep explained.

“The reality is that disk-based systems are just too slow. You can do all these optimizations to your data, but in the end what a company needs is 10 times to 100 times more improvement and in-memory computing is the only way to get that scale and performance,” Abe Kleinfeld, president and CEO of GridGain Systems, an in-memory computing platform provider, added. “The good news is that computer hardware doesn’t cost that much anymore. It continues to get cheaper and cheaper. You can fit a lot of memory in modern computers today.”

According to the research firm Forrester, an in-memory database refers to “a database that stores all or most critical data in DRAM, flash, and SSD on either a single or distributed server to support various types of workloads, including transactional, operational, and/ or analytical workloads, running on-premises or in the cloud.”

While in-memory systems have been around for years, the costs associated with it placed it in very niche applications for very specialized tasks such as critical systems, explained Keep. Thanks to lower memory prices, Forrester principal analyst Noel Yuhanna sees in-memory technologies moving more towards complex mobile, web and interactive workloads such as real-time analytics, fraud detection, mobile ads and IoT apps.

“We find that everyone wants to run operational reporting and insights quickly to make better business decisions. This is where in-memory comes in.