Nikita Ivanov

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Nikita Ivanov
Position:
Founder & CTO, GridGain Systems
Bio:

Nikita Ivanov is founder and CTO of GridGain Systems, started in 2007 and funded by RTP Ventures and Almaz Capital. Nikita provides the vision and leadership at GridGain to develop the world’s top in-memory computing platform, now used by thousands of organizations around the globe to power business-critical systems and enable digital transformation initiatives.

Nikita has over 20 years of experience in software application development, building HPC and middleware platforms, and 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 the Baltic State Technical University, Saint Petersburg, Russia.

Bio:

Nikita Ivanov is founder and CTO of GridGain Systems, started in 2007 and funded by RTP Ventures and Almaz Capital. Nikita provides the vision and leadership at GridGain to develop the world’s top in-memory computing platform, now used by thousands of organizations around the globe to power business-critical systems and enable digital transformation initiatives.

Nikita has over 20 years of experience in software application development, building HPC and middleware platforms, and 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 the Baltic State Technical University, Saint Petersburg, Russia.

In-Memory Compute and Data Grids serve as the fundamental components of an in-memory architecture. The objective of In-Memory Data Grids (IMDG) is to ensure exceptionally high data availability by storing it in memory in a highly distributed and parallelized manner. By loading terabytes of data into memory, IMDGs can effectively handle most of the requirements for processing Big Data today.…
There are two significant categories in in-memory computing: In-Memory Database and In-Memory Data Grids. This post aims to present a concise version of thoughts on this topic, with insights gained from a recent analyst call aiding in organizing the information. Nomenclature of In-Memory Database vs In-Memory Data Grid Let's start by clarifying the terminology and buzzwords. The term "In-…
Businesses today are increasingly complex leading to slow performance which negatively impacts customer experiences, productivity, and ultimately revenue. An in-memory data fabric addresses data complexity head-on. Companies today are facing a significant problem – their reliance on disk-based data stores are slowing down performance and costing them valuable time and money. Enter GridGain’s…
After five days (and eleven meetings) with new customers in Europe and the Middle East, I think the 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,…