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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)

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)

In-Memory Technology & Wave of Innovation By @GridGain | @CloudExpo [#BigData]

In-Memory Technology Will Open the Doors to a Wave of Innovation by Abe Kleinfeld and Nikita Ivanov Gordon E. Moore's famously predicted tech explosion was prophetic, but it may have hit a snag.  While the number of transistors on integrated circuits has doubled approximately every two years since his 1965 paper, the ability to process and transact on data hasn't. We're now ingesting data faster than we can make sense of it, leaving computing at an impasse. Without a new approach, the innovation promised by the combination of Big Data and internet scale may be like the flying car... (more)

Columnar vs. Key-Value Storage Models

What are the performance differences between in-memory columnar databases like SAP HANA and GridGain's In-Memory Database (IMDB) utilizing distributed key-value storage? This questions comes up regularly in conversations with our customers and the answer is not very obvious. Storage Models First off, let's clearly state that we are talking about storage model only and its implications on performance for various use cases. It's important to note that: Storage model doesn't dictate of preclude a particular transactionality or consistency guarantees; there are columnar databases tha... (more)