Welcome!

Related Topics: Containers Expo Blog, Java IoT, Microservices Expo, Linux Containers, SDN Journal

Containers Expo Blog: Blog Post

In-Memory Computing: In Plain English

Explaining in-memory computing and defining what in-memory computing is really about

After five days (and eleven meetings) with new customers in Europe, Russia, and the Middle East, I think time is right for another refinement of in-memory computing's definition. To me, it is clear that our industry is lagging when it comes to explaining in-memory computing to potential customers and defining what in-memory computing is really about. We struggle to come up with a simple, understandable definition of what in-memory computing is all about, what problems it solves, and what uses are a good fit for the technology.

In-Memory Computing: What Is It?
In-memory computing means using a type of middleware software that allows one to store data in RAM, across a cluster of computers, and process it in parallel. Consider operational datasets typically stored in a centralized database which you can now store in "connected" RAM across multiple computers. RAM, roughly, is 5,000 times faster than traditional spinning disk. Add to the mix native support for parallel processing, and things get very fast. Really, really, fast.

RAM storage and parallel distributed processing are two fundamental pillars of in-memory computing.

RAM storage and parallel distributed processing are two fundamental pillars of in-memory computing. While in-memory data storage is expected of in-memory technology, the parallelization and distribution of data processing, which is an integral part of in-memory computing, calls for an explanation.

Parallel distributed processing capabilities of in-memory computing are... a technical necessity. Consider this: a single modern computer can hardly have enough RAM to hold a significant dataset. In fact, a typical x86 server today (mid-2014) would have somewhere between 32GB to 256GB of RAM. Although this could be a significant amount of memory for a single computer, that's not enough to store many of today's operational datasets that easily measure in terabytes.

To overcome this problem in-memory computing software is designed from the ground up to store data in a distributed fashion, where the entire dataset is divided into individual computers' memory, each storing only a portion of the overall dataset. Once data is partitioned - parallel distributed processing becomes a technical necessity simply because data is stored this way.

And while it makes the development of in-memory computing software challenging (literally fewer than 10 companies in the world have mastered this type of software development) - end users of in-memory computing seeking dramatic performance and scalability increas benefit greatly from this technology.

In-Memory Computing: What Is It Good For?
Let's get this out of the way first: if one wants a 2-3x performance or scalability improvements - flash storage (SSD, Flash on PCI-E, Memory Channel Storage, etc.) can do the job. It is relatively cheap and can provide that kind of modest performance boost.

To see, however, what a difference in-memory computing can make, consider this real-live example...

Last year GridGain won an open tender for one of the largest banks in the world. The tender was for a risk analytics system to provide real-time analysis of risk for the bank's trading desk (common use case for in-memory computing in the financial industry). In this tender GridGain software demonstrated one billion (!) business transactions per second on 10 commodity servers with the total of 1TB of RAM. The total cost of these 10 commodity servers? Less than $25K.

Now, read the previous paragraph again: one billion financial transactions per second on $25K worth of hardware. That is the in-memory computing difference - not just 2-3x times faster; more than 100x faster than theoretically possible even with the most expensive flash-based storage available on today's market (forget about spinning disks). And 1TB of flash-based storage alone would cost 10x of entire hardware setup mentioned.

Importantly, that performance translates directly into the clear business value:

  • you can use less hardware to support the required performance and throughput SLAs, get better data center consolidation, and significantly reduce capital costs, as well as operational and infrastructure overhead, and
  • you can also significantly extend the lifetime of your existing hardware and software by getting increased performance and improve its ROI by using what you already have longer and making it go faster.

And that's what makes in-memory computing such a hot topic these days: the demand to process ever growing datasets in real-time can now be fulfilled with the extraordinary performance and scale of in-memory computing, with economics so compelling that the business case becomes clear and obvious.

In-Memory Computing: What Are the Best Use Cases?
I can only speak for GridGain here but our user base is big enough to be statistically significant. GridGain has production customers in a wide variety of industries:

  • Investment banking
  • Insurance claim processing & modeling
  • Real-time ad platforms
  • Real-time sentiment analysis
  • Merchant platform for online games
  • Hyper-local advertising
  • Geospatial/GIS processing
  • Medical imaging processing
  • Natural language processing & cognitive computing
  • Real-time machine learning
  • Complex event processing of streaming sensor data

And we're also seeing our solutions deployed for more mundane use cases, like speeding the response time of a student registration system from 45 seconds to under a half-second.

By looking at this list it becomes pretty obvious that the best use cases are defined not by specific industry but by the underlying technical need, i.e. the need to get the ultimate best and uncompromised performance and scalability for a given task.

In many of these real-life deployments in-memory computing was an enabling technology, the technology that made these particular systems possible to consider and ultimately possible to implement.

The bottom line is that in-memory computing is beginning to unleash a wave of innovation that's not built on Big Data per se, but on Big Ideas, ideas that are suddenly attainable. It's blowing up the costly economics of traditional computing that frankly can't keep up with either the growth of information or the scale of demand.

As the Internet expands from connecting people to connecting things, devices like refrigerators, thermostats, light bulbs, jet engines and even heart rate monitors are producing streams of information that will not just inform us, but also protect us, make us healthier and help us live richer lives. We'll begin to enjoy conveniences and experiences that only existed in science fiction novels. The technology to support this transformation exists today - and it's called in-memory computing.

More Stories By Nikita Ivanov

Nikita Ivanov is founder and CEO of GridGain Systems, started in 2007 and funded by RTP Ventures and Almaz Capital. Nikita has led GridGain to develop advanced and distributed in-memory data processing technologies – the top Java in-memory computing platform starting every 10 seconds around the world today.

Nikita has over 20 years of experience in software application development, building HPC and middleware platforms, contributing to the efforts of other startups and notable companies including Adaptec, Visa and BEA Systems. Nikita was one of the pioneers in using Java technology for server side middleware development while working for one of Europe’s largest system integrators in 1996.

He is an active member of Java middleware community, contributor to the Java specification, and holds a Master’s degree in Electro Mechanics from Baltic State Technical University, Saint Petersburg, Russia.

Latest Stories
SYS-CON Events announced today that Nihon Micron will exhibit at the Japan External Trade Organization (JETRO) Pavilion at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Nihon Micron Co., Ltd. strives for technological innovation to establish high-density, high-precision processing technology for providing printed circuit board and metal mount RFID tags used for communication devices. For more inf...
SYS-CON Events announced today that Massive Networks, that helps your business operate seamlessly with fast, reliable, and secure internet and network solutions, has been named "Exhibitor" of SYS-CON's 21st International Cloud Expo ®, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. As a premier telecommunications provider, Massive Networks is headquartered out of Louisville, Colorado. With years of experience under their belt, their team of...
SYS-CON Events announced today that Suzuki Inc. will exhibit at the Japan External Trade Organization (JETRO) Pavilion at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Suzuki Inc. is a semiconductor-related business, including sales of consuming parts, parts repair, and maintenance for semiconductor manufacturing machines, etc. It is also a health care business providing experimental research for...
"Our strategy is to focus on the hyperscale providers - AWS, Azure, and Google. Over the last year we saw that a lot of developers need to learn how to do their job in the cloud and we see this DevOps movement that we are catering to with our content," stated Alessandro Fasan, Head of Global Sales at Cloud Academy, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
21st International Cloud Expo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Me...
Enterprises are moving to the cloud faster than most of us in security expected. CIOs are going from 0 to 100 in cloud adoption and leaving security teams in the dust. Once cloud is part of an enterprise stack, it’s unclear who has responsibility for the protection of applications, services, and data. When cloud breaches occur, whether active compromise or a publicly accessible database, the blame must fall on both service providers and users. In his session at 21st Cloud Expo, Ben Johnson, C...
Many organizations adopt DevOps to reduce cycle times and deliver software faster; some take on DevOps to drive higher quality and better end-user experience; others look to DevOps for a clearer line-of-sight to customers to drive better business impacts. In truth, these three foundations go together. In this power panel at @DevOpsSummit 21st Cloud Expo, moderated by DevOps Conference Co-Chair Andi Mann, industry experts will discuss how leading organizations build application success from all...
SYS-CON Events announced today that mruby Forum will exhibit at the Japan External Trade Organization (JETRO) Pavilion at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. mruby is the lightweight implementation of the Ruby language. We introduce mruby and the mruby IoT framework that enhances development productivity. For more information, visit http://forum.mruby.org/.
Cloud-based disaster recovery is critical to any production environment and is a high priority for many enterprise organizations today. Nearly 40% of organizations have had to execute their BCDR plan due to a service disruption in the past two years. Zerto on IBM Cloud offer VMware and Microsoft customers simple, automated recovery of on-premise VMware and Microsoft workloads to IBM Cloud data centers.
Why Federal cloud? What is in Federal Clouds and integrations? This session will identify the process and the FedRAMP initiative. But is it sufficient? What is the remedy for keeping abreast of cutting-edge technology? In his session at 21st Cloud Expo, Rasananda Behera will examine the proposed solutions: Private or public or hybrid cloud Responsible governing bodies How can we accomplish?
Today traditional IT approaches leverage well-architected compute/networking domains to control what applications can access what data, and how. DevOps includes rapid application development/deployment leveraging concepts like containerization, third-party sourced applications and databases. Such applications need access to production data for its test and iteration cycles. Data Security? That sounds like a roadblock to DevOps vs. protecting the crown jewels to those in IT.
SYS-CON Events announced today that Cedexis will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Cedexis is the leader in data-driven enterprise global traffic management. Whether optimizing traffic through datacenters, clouds, CDNs, or any combination, Cedexis solutions drive quality and cost-effectiveness.
Elon Musk is among the notable industry figures who worries about the power of AI to destroy rather than help society. Mark Zuckerberg, on the other hand, embraces all that is going on. AI is most powerful when deployed across the vast networks being built for Internets of Things in the manufacturing, transportation and logistics, retail, healthcare, government and other sectors. Is AI transforming IoT for the good or the bad? Do we need to worry about its potential destructive power? Or will we...
SYS-CON Events announced today that B2Cloud will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. B2Cloud specializes in IoT devices for preventive and predictive maintenance in any kind of equipment retrieving data like Energy consumption, working time, temperature, humidity, pressure, etc.
In his session at @ThingsExpo, Greg Gorman is the Director, IoT Developer Ecosystem, Watson IoT, will provide a short tutorial on Node-RED, a Node.js-based programming tool for wiring together hardware devices, APIs and online services in new and interesting ways. It provides a browser-based editor that makes it easy to wire together flows using a wide range of nodes in the palette that can be deployed to its runtime in a single-click. There is a large library of contributed nodes that help so...