Re-Imagining Ultimate Performance

It’s been somewhat quiet here on the GridGain front for a few months, and for good reason!

We just announced closing a $10M Series B investment and bringing an awesome new investor on board. In the last 6 months we not only closed the new round, we also rebuilt and tripled our sales and business development team, retooled our marketing, released new products, and have 3 other products in the development pipeline scheduled for announcement later this year.

But I think the most important thing we’ve accomplished so far is the crystallization and validation of our vision and strategy around our end-to-end stack for In-Memory Computing.

In-Memory Computing


Kirill Sheynkman, one of our board members and an investor, probably put it the best: “In-Memory Computing is characterized by using high-performance, integrated, distributed memory systems to manage and transact on large-scale data sets in real-time, orders of magnitude faster than possible with traditional disk-based technologies”.

In-Memory Computing is a new way to compute and store data, a type of revolution we haven’t witnessed since the early 1970s when IBM released the “winchester” disk IBM 3340 and the era of HDDs officially began. Today, we are in same transitional period moving away from HDDs/SSDs or other block devices to a new era of DRAM-based storage -- creating a tidal wave of innovation in software.

Just as the development of cheap HDDs pushed forward the database industry in the 1970s and SQL was born, today relentless data growth coupled with real time requirements for data processing necessitate a move to in-memory processing, massive parallelization and unstructured data.

Unlike companies around us, here at GridGain, we strongly believe that In-Memory Computing is a paradigm shift. It’s not just a single product, enhancement or feature add-on -- it’s a different way to think about how we deal with exponentially growing data sets and unrelenting appetite for actionable and real-time data intelligence and analysis.

Here at GridGain we are leading this revolution and we have the vision and technology to do just that.


End-to-End In-Memory Computing Stack


Most of today’s business applications dealing with large data sets (outside of legacy batch processing) are built to process three different types of payload:

  • Database or system of record,
  • High performance, parallelized computations, and
  • Real time, high frequency streaming and CEP data processing

These three types of payload (or combination of them) are at the core of practically every big data end user system built today. Providing in-memory products directly addressing these three types of payload is what makes GridGain an end-to-end In-Memory Computing stack

In-Memory Computing Stack

What’s also important is that we have built our product line from the ground up. We didn’t acquire some fledging startup, gain pieces of technology from a merger, or revamp some dying open source project to quickly fill a gap in the product line. Every product we have is built by the same team, from the same base and came about as a natural evolution of our product line in the last 7 years.

That’s why you have absolutely zero learning curve when moving from product to product. Our customers often note just how cohesive and unified our products “feel” to them: familiar APIs, principles and concepts, same configuration, same management, same installation, same documentation... and the same engineers providing top-notch support.

Platforms don’t get built by haphazardly stitching together random pieces of software. They grow organically over time in the hands of dedicated product and engineering teams.


Integrated Products


A few years ago we noticed one class of customers that want the increased speed and scalability benefits of in-memory computing but just didn’t have the appetite for the development and simply shied away from using any in-memory computing products at all.

Instead of losing these customers, we’ decided to pick some of the most common use cases and create highly integrated, plug-n-play product, i.e accelerators, so that they can enjoy the benefits of in-memory computing without the need for development cycles or potential changes in their systems.

That’s how our In-Memory Hadoop and In-Memory NoSQL Accelerators came about. And soon we’ll add storage accelerators to the mix in a few months.

A unique characteristic of GridGain’s integrated products is the “no assembly required” nature in which they integrate. They deliver all the scalability and performance advantages of GridGain’s In-Memory Computing stack with zero code changes and minimal configuration changes to the host products.

Management and Monitoring


No stack can be truly considered end-to-end without incorporating a single and unified management and monitoring system. GridGain prides itself on providing the #1 DevOps support technology among any in-memory computing company with its Visor Administration Console. GridGain’s Visor is a GUI-and CLI-based system that provides deep runtime management, monitoring, and operational command and control for running any production GridGain product.

visor_dash2

Time Is Now


Einstein got it right when he said imagination is more important than knowledge. At GridGain, we’ve re-imagined ultimate performance as In-Memory Computing so that you can re-imagine your company for today’s increasingly competitive business environment.

GridGain understands that In-Memory Computing is more than the latest tech trend. It’s the next major shift for an increasingly hyper business world in which organizations face problems that traditional technology can’t even fathom, much less solve. In-Memory Computing is a step all organizations must take to remain competitive, and we’re ready to take that step with you.

You’ll never need to analyze less data. The speed of business will never be slower. Your business challenges will never be simpler. Now is the time for In-Memory Computing – only GridGain gives you a complete solution without any compromises.










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