Webinars on In-Memory Computing

GridGain® webinars present information on a variety of in-memory computing topics, and are often co-hosted with other in-memory computing customers or thought leaders. Topics include in-depth analyses and recommendations for common issues faced by in-memory computing developers, enterprise architects, CIO/CTOs, and other enterprise decision-makers. Different approaches for implementing solutions are reviewed, including solutions using the GridGain in-memory computing platform and Apache® Ignite. The webinars cover enterprise use cases such as high-frequency trading, omnichannel customer engagement, the Internet of Things (IoT), financial services, application performance and scaling, fast data, and more.

All GridGain webinars are archived and available for free online.

On Demand Webinar
Denis Magda
Learn how Kubernetes can orchestrate a distributed database or in-memory computing solutions using Apache Ignite as an example.
On Demand Webinar
Akmal B. Chaudhri
In this webinar, Akmal Chaudhri, GridGainTechnical Evangelist, will introduce the fundamental capabilities and components of an in-memory computing platform with a focus on Apache Ignite, and demonstrate how to apply the theory in practice. With increasingly advanced coding examples, architects and developers will learn about:
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On Demand Webinar
Akmal B. Chaudhri
Lors de ce webinar, Akmal Chaudhri, Promoteur de Produit pour GridGain Systems, présentera les capacités et les composantes fondamentales de la plateforme d’In-Memory Computing avec Apache Ignite et vous expliquera comment passer de la théorie à la pratique.
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On Demand Webinar
Ivan Rakov & Rob Meyer
When deployed properly, it's hard to beat a horizontal distributed architecture's scalability, availability and reliability. The trick is deploying it properly to compensate for individual node, data or network failures. Learn some of the best practices for setting up your clusters properly to maximize availability, reliability and flexibility for future needs.
On Demand Webinar
Denis Magda
Once you've put in-memory computing in place to add speed and scale to your existing applications, the next step is to innovate and improve the customer experience. Join us for part 2 of the in-memory computing best practices series. Learn how companies build new HTAP applications with in-memory computing that leverage analytics within transactions to improve business outcomes.
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On Demand Webinar
Denis Magda
It's hard to improve the customer experience when your existing applications can't handle the ever-increasing customer loads, are inflexible to change and don't support the real-time analytics or machine learning needed to improve the experience at each step of the way. Join us for part 1 of the in-memory computing best practices series.
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On Demand Webinar
Akmal B. Chaudhri
Apache Ignite Release 2.4 added built-in machine learning (ML) and deep learning (DL). It not only eliminates any delays caused by transferring data to a different database or store.  It delivers near real-time performance by running a variety of ML and DL algorithms in place, in memory, that are optimized for collocated processing.
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On Demand Webinar
Akmal B. Chaudhri
Learn how Apache Ignite™ simplifies development and improves performance for Apache Spark™. This session will explain how Apache Spark and Ignite are integrated, and how they are used to together for analytics, stream processing and machine learning.  By the end of this session you will understand:
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On Demand Webinar
Matt Aslett & Rob Meyer
The need to engage more intelligently in real-time during each transaction or interaction, whether it's to add personalization and recommend products or to help improve the overall customer experience across multiple channels, is driving the need for new infrastructure with much lower latency and much higher scalability.
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On Demand Webinar
Denis Magda
The 10x growth of transaction volumes, 50x growth in data volumes and drive for real-time visibility and responsiveness over the last decade have pushed traditional technologies including databases beyond their limits.
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On Demand Webinar
Denis Magda
The need for real-time computing has resulted in the growth of many different in-memory computing (IMC) technologies. This includes caches, in-memory data grids, in-memory databases, streaming technologies and broader IMC platforms.  But what are the best technologies for each type of project? Learn about your options from one of the leading IMC veterans.
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On Demand Webinar
Denis Magda
It used to be that the only way to improve application performance was to add a cache. But caches like Redis don't understand SQL. They require you to modify your applications with non-SQL coding and data models, and copy and synch data across two different models. They don't support ACID transactions very well. And they have their limits when it comes to scalability.
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On Demand Webinar
Valentin Kulichenko
Apache Ignite native persistence is a distributed ACID and SQL-compliant store that turns Apache Ignite into a full-fledged distributed SQL database.
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On Demand Webinar
Akmal B. Chaudhri
Learn some of the best practices companies have used to increase performance of existing or new SQL-based applications up to 1,000x, scale to millions of transactions per second and handle petabytes of data by adding Apache® Ignite™.
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On Demand Webinar
Denis Magda
Distributed platforms like Apache® Ignite™ rely on a horizontal “scale-out” architecture where you dynamically add more machines to achieve near-linear, elastic scalability. But how does it really work? What are its limits? And how can you optimize performance and scalability?
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