Learn About GridGain® and Apache® Ignite

The GridGain technical presentations below are designed to help you understand, configure, and deploy GridGain and Apache Ignite in-memory computing solutions for use in your application production environment. They have been developed and posted by GridGain and other in-memory computing experts. These presentations are a free resource that can be watched more than once.

In this webinar, using examples, we will cover the specifics of how to use Node.js with Ignite, including:
In this session, you will understand best practices about how to: Configure Ignite and GridGain for deployment, management and monitoring Leverage log files during troubleshooting Use monitoring interfaces and tools such as JMX, Visor and Web Console Identify and fix top errors for newly installed and existing deployments
Topics covered include: Transactional SQL Deep learning with TensorFlow Thin client support for Node.js, Python, PHP Transparent encryption for Ignite persistence
By the end of this session you'll understand: How an IMDG adds speed and scale without requiring you to rip out and replace existing databases or applications Typical projects where an IMDG makes sense as a first project Best practices implementing the first IMDG project and preparing for future projects including real-time analytics, new applications and APIs,
Learn how companies have been using Apache® Ignite™ to add in-memory speed and unlimited horizontal scale to SQL with no rip-and-replace of the underlying database. This session will explain how to:
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 how.
With real-time streaming analytics there is no room for staging or disk.  Learn the best practices used for real-time stream ingestion, processing and analytics using Apache® Ignite™, GridGain®, Kafka™, Spark™ and other technologies. 
This webinar will explain with examples how to:
This 60-minute hands-on session will: Explain how GridGain Cloud works Walk through step-by-step how to create an account, start a cluster, load and query data using ANSI-99 SQL Demonstrate how to build applications that accesses data using a REST API, ODBC/JDBC or a binary thin client
Learn how Kubernetes can orchestrate a distributed database or in-memory computing solutions using Apache Ignite as an example.
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.
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…
Join us for part 1 of the in-memory computing best practices series. Learn how companies are not only adding speed and scale without ripping out, rewriting or replacing their existing applications and databases, but also how they're setting themselves up for future projects to improve the customer experience. This webinar will explain with examples:
Learn more about the role of In-Memory Computing in supporting the real-time transactional, analytical and engagement needs for digital business and improving the customer experience.