Stream Processing Meetup

Come join us for this informative Stream Processing Meetup and Networking Event: Presentations + Networking with drinks and food!

Talk #1: “Easy and Fast Stream Processing” by Fuad Malikov, Co-Founder at Hazelcast

In this session you will learn all about directed acyclic graph (DAG) and why it is so powerful for Big Data processing. We will walk you through the evolution of Big Data computing from sequential to DAG as well as other techniques such as SP/SC, Cooperative Multithreading, Data Locality, In-Memory sources and sinks, and WaitFree algorithms that power the third generation of Big Data processing.

This presentation will also feature an introduction to Hazelcast JET, an Apache 2 licensed, DAG-based platform for in-memory streaming and fast batch processing that illustrates many of the techniques found in a third generation Big Data platform.

We will walk you through coding common tasks in Java and then step it up to writing full-blown applications in less than a hundred lines of Java code, for applications such as Bitcoin, Twitter sentiment analysis and real-time monitoring of worldwide commercial aircraft.

Talk #2: “Faster Java Without Pauses For Stream Processing” by Simon Ritter, Deputy CTO at Azul Systems
The Java platform is perfect for addressing the needs of big data and stream processing and the Java Virtual Machine (JVM) provides many advantages for developing these types of applications.

Managed memory, which results in garbage collection (GC) pauses that are both non-deterministic and potentially very long often results in traditional JVM deployments designed to alleviate these issues, not solve them.

In this session, we will explain how the Zing JVM from Azul Systems solves the problem of GC as well as providing better overall performance by using the Falcon JIT compiler. Find out how applications running on Zing start fast, go faster and stay fast!

PLEASE RSVP VIA THIS LINK: https://hazelcast.com/events/real-time-stream-processing-meetup-nyc/