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From the Founder and CEO of GridGain Systems

Nikita Ivanov

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Top Stories by Nikita Ivanov

If you know anything about Hadoop architecture - the task seemed daunting to us and it proved to be one of the most challenging engineering feat that we have accomplished so far. After almost 24 months of development, tens of thousands of lines of Java, Scala and C++ code, multiple design iterations, several releases and dozens of benchmarks later we have the product that can deliver real-time performance to Hadoop with only minimal integration and no ETL required. Backed-up by customer deployments that prove our performance claims and validate our architecture. Here's how we did it. The Idea - In-Memory Hadoop Accelerator Hadoop is based on two key technologies: HDFS for storing data, and MapReduce for processing that data in parallel. Everything else in Hadoop itself and the entire ecosystem coalesce around these two technologies. Both - HDFS and MapReduce - were ... (more)

The State of Real-time Analytics in Financial Services By @GridGain [#BigData]

The State of Real-time Analytics in Financial Services My company, GridGain, recently announced the results of a survey that asked close to 200 IT decision-makers - including project managers, network managers, software and business analysts, and other technology professionals working in the financial services industry - about their companies' attitudes, practices and challenges around data technology, with a focus on the state of the industry's adoption of real time analytics technologies. Here's what we found: In the report - A Cautious Revolution: Financial Services' Prudent E... (more)

Four Myths of In-Memory Computing

Let's start at... the beginning. What is the in-memory computing? Kirill Sheynkman from RTP Ventures gave the following crisp definition which I like very much: "In-Memory Computing is based on a memory-first principle utilizing high-performance, integrated, distributed main memory systems to compute and transact on large-scale data sets in real-time - orders of magnitude faster than traditional disk-based systems." The most important part of this definition is "memory-first principle". Let me explain... Memory-First Principle Memory-first principle (or architecture) refers to a... (more)

In-Memory Database vs. In-Memory Data Grid By @GridGain | @CloudExpo [#BigData]

A few months ago, I spoke at the conference where I explained the difference between caching and an in-memory data grid. Today, having realized that many people are also looking to better understand the difference between two major categories in in-memory computing: In-Memory Database and In-Memory Data Grid, I am sharing the succinct version of my thinking on this topic - thanks to a recent analyst call that helped to put everything in place  TL;DR Skip to conclusion to get the bottom line. Nomenclature Let's clarify the naming and buzzwords first. In-Memory Database (IMDB) is a ... (more)

In-Memory Computing By @GridGain | @CloudExpo [#BigData]

The Facts and Fiction of In-Memory Computing In the last year, conversations about In-Memory Computing (IMC) have become more and more prevalent in enterprise IT circles, especially with organizations feeling the pressure to process massive quantities of data at the speed that is now being demanded by the Internet. The hype around IMC is justified: tasks that once took hours to execute are streamlined down to seconds by moving the computation and data from disk, directly to RAM. Through this simple adjustment, analytics are happening in real-time, and applications (as well as th... (more)