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GridGain for Sberbank Architecture in Financial Services [Videos]

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GridGain for Sberbank Architecture in Financial Services [Videos]

Using Apache Ignite for scaling at banks in Europe by enabling fast in-memory caching and colocated data processing.

· Database Zone
Free Resource

Read why times series is the fastest growing database category.

Speakers: Dmitriy Setrakyan, Founder and Chief Product Officer, GridGain and Mikhail Khasin, Senior Managing Director & Head of Core banking Transformation Program, Sberbank

This presentation will be shared between Dmitriy Setrakyan, founder and chief product officer at GridGain, and Mikhail Khasin, senior managing director and head of the Core Banking Transformation Program at Sberbank, one of the largest banks in Eastern Europe.

In this section, we will cover how GridGain and Apache Ignite helped Sberbank achieve scalability and performance based on distributed in-memory caching and colocated data processing. We will closely dissect the data grid architecture and how it was applied. We will also go over a few gotchas to watch out for, as well as recommend several best-practice approaches, including colocated data, colocated computing, fault tolerance, distributed queries, deadlock-free transactions, and more. If you are interested in real-time scalable in-memory architectures, then this section is for you.


Learn how to get 20x more performance than Elastic by moving to a Time Series database.

Topics:
in-memory ,jvm ,java

Published at DZone with permission of Nikita Ivanov, DZone MVB. See the original article here.

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