Webinars on In-Memory Computing

GridGain® Systems offers webinars on in-memory computing which describe how it is addressing current and future use cases driven by digital transformation and omnichannel customer experience initiatives.

Alexey Kukushkin & Rob Meyer
Learn some of the best practices companies have used for making Apache Ignite and Apache Kafka scale. Making stream processing scale requires making all the components—including messaging, processing, storage—scale together.   During this 1-hour webinar by GridGain Systems Professional Services Consultant Alexey Kukushkin, you will learn about:
Akmal B. Chaudhri
In this presentation, attendees will learn about Apache Ignite and the GridGain in-memory computing platform, which is built on Apache Ignite, and about the key capabilities and features important for financial applications, including ACID compliance, SQL compatibility, persistence, replication, security, fault tolerance, fraud detection and more.
Andrey Evsukov & Rob Meyer
Once your Apache® Ignite™ or GridGain® cluster goes in production, you will need to keep an eye on its state. You will also have to manage your deployment throughout its lifetime. These tasks might seem challenging, but managing and monitoring distributed systems is not cumbersome if you have a right toolkit.
Denis Magda
Learn the best practices used for real-time stream ingestion, processing and analytics using Apache® Ignite™, GridGain®, Kafka™, Spark™ and other technologies.  Join GridGain System’s Director of Product Management and Apache Ignite PMC Chair Denis Magda for this 1-hour webinar
Akmal B. Chaudhri
Lors de ce Webinar en Anglais, Akmal Chaudhri, Promoteur des Produits GridGain System et Apache® Ignite™, 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. Grâce à des exemples de plus en plus codés, les architectes et développeurs apprendront :Le…
Akmal B. Chaudhri
In this webinar, Akmal Chaudhri, Technology Product Evangelist for GridGain and Apache Ignite, will introduce the fundamental capabilities and components of a distributed, in-memory computing platform. With increasingly advanced coding examples, architects and developers will learn about:
Lucas Beeler
This 1-hour webinar presented by GridGain System’s Sr. Technical Consultant Lucas Beeler will discuss architectural best practices many companies have used in their journey to multi-cluster computing applications.
Akmal B. Chaudhri & Rob Meyer
GridGain Cloud, which enables companies to create an in-memory SQL and key-value database in minutes, is now in Beta. Learn from the experts how to use GridGain Cloud, and get up and running. This 60-minute hands-on session will:
Denis Magda
In-memory computing technologies such as in-memory data grids (IMDG) and databases (IMDB), NoSQL and NewSQL databases can make so many things easier for a developer. But implementing DevOps for these distributed technologies and the related storage can be difficult. Luckily Kubernetes has come to the rescue!
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:
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.
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.
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.
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.
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.