Nikita Ivanov

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Top Stories by Nikita Ivanov

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 the development of applications) are working at-pace with this new standard of technology and speed. Despite becoming both more cost-effective and accepted within enterprise computing, there are still a small handful of falsehoods that confuse even the most technical of individuals in enterprise IT. Myth: In-memory computing is about dat... (more)

In-Memory Computing: In Plain English

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 computin... (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)

Hadoop – 100x Faster

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 d... (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)