Past GridGain Meetups

You can see the presentations and information from past GridGain meetups around the world below.

In this talk, we describe and show how to use Apache Ignite and JBoss Drools to design a complex event processing (CEP) solution. The solution processes and correlates millions of events per second from a publish/subscribe message broker and another kind of events streamer.
Join Chicago PostgreSQL Meetup Group to learn about some of the internal mechanisms that distributed systems use to achieve the required goals. Val Kulichenko describes the minimal architecture of distributed data storage—the main components and how the components work together.
Join London Java Community and Val Kulichenko to learn more about distributed databases.  Distributed databases are becoming more and more popular. Social networks, online banking, and retail—these are only a few examples of applications that might require horizontal scalability to achieve the performance, capacity, and availability that organizations require.
Join Boston Java Meetup on March 29
Building a scalable, multi-tenant backend for a Java-based, ML-driven Jira Cloud application imposes many requirements on the underlying technology stack. It is not uncommon to fulfill the requirements by combining pieces of technology—such as SQL and NoSQL databases, ORM tools, message brokers, load balancers, caching layers, ML pipelines, and web servers.
Every day, millions of people travel by train through the Netherlands—on one of the busiest rail infrastructures in Europe. More than 10,000 train movements are performed daily. Planning for all these train rides and designing a timetable that avoids hazardous situations is a challenge.
Join Apache Ignite community on December 8 to learn more about using Ignite for the bank's backend and how to work with Ignite compute grid and Drool. 
Join the biggest Israeli Java Users Meetup on November 30 as Denis Maga describes and demonstrates three essential capabilities of in-memory computing—with code samples based on Apache Ignite: - Data partitioning: to use all of a cluster’s memory and CPU resources. - Affinity co-location: to avoid data shuffling and use highly performant, distributed SQL queries.
Apache Ignite is designed as a black box that hides the complexities of distributed databases. However, by knowing how internal components work and how the distributed databases function, you can pave the way for advanced optimizations and sophisticated solutions that are powered by Ignite.
“Questions and answers” is an important part of our gatherings. Developers and users share experiences and best practices, and together we create Apache Ignite. So, let's give our questions the time that they deserve! On October 20, join a special community session and ask experts about Ignite features, configuration, and architecture.
Join Virtual Java Group to be introduced to the fundamental capabilities of distributed, in-memory systems and will learn how to tap into your cluster’s resources:
Join London Java Community to be introduced to the fundamental capabilities of distributed, in-memory systems and will learn how to tap into your cluster’s resources: Denis Magda will describe and demonstrate three essential capabilities of in-memory computing—with code samples based on Apache Ignite:
Registration page: https://www.meetup.com/Bay-Area-In-Memory-Computing/events/273169233/
September 15 Val Kulichenko, a community old-timer and the Ignite 3.0 release manager, will open the discussion by covering major changes that are proposed for release 3.0: ‒ Schema-first approach ‒ Dynamic configuration ‒ SQL API ‒ Modularization ‒ Cleanup ‒ Native Image support for GraalVM
For some cases, Apache Ignite is the perfect application. However, also, for some cases, Apache Ignite can be a disappointment. In this talk, Dmitry Pavlov discusses some popular and less-than popular use cases. The presentation focuses on the needs of developers and architects who face application-performance problems. Considered use cases: