Get Started

Get Started

These guides demonstrate how to get started quickly with Hazelcast IMDG and Hazelcast Jet.

Hazelcast IMDG

Learn how to store and retrieve data from a distributed key-value store using Hazelcast IMDG. In this guide you’ll learn how to:

  • Create a cluster of 3 members.
  • Start Hazelcast Management Center
  • Add data to the cluster using a sample client in the language of your choice
  • Add and remove some cluster members to demonstrate data balancing capabilities of Hazelcast

Hazelcast Jet

Learn how to build a distributed data processing pipeline in Java using Hazelcast Jet. In this guide you’ll learn how to:

  • Install Hazelcast Jet and form a cluster on your computer
  • Build a simple pipeline that receives a stream of data, does some calculations and outputs some results
  • Submit the pipeline as a job to the cluster and observe the results
  • Scale the cluster up and down while the job is still running

About the Author

Vladimir Schreiner

Vladimir Schreiner

Vladimir is a product manager with an engineering background and deep expertise in stream processing and real-time data pipelines. Ten years of building internal software platforms and development infrastructure have made him passionate about new technologies and finding ways to simplify data processing. Vladimir co-authored two white papers on the topic: Understanding Stream Processing: Fast Processing of Infinite and Big Data, and A Reference Guide to Stream Processing. His tutorial video on stream processing and real-time data pipelines discusses the building blocks of a stream processing pipeline and demonstrates how developers can write a full-blown streaming pipeline in less than a hundred lines of Java code for a variety of applications. Vladimir is also a lecturer with the Czechitas Foundation, whose mission is to inspire women and girls to explore the world of information technology. Czechitas Foundation teaches coding in various programming languages, software testing, and data analysis.

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How Hazelcast Jet Compares to Apache Spark

Vladimir Schreiner
by Vladimir Schreiner

“How Jet compares to Spark” and “why should I choose Jet over Spark” are arguably the most frequent questions I’ve been asked during the talks and workshops. While it is hard to assess the product fit without focusing on a concrete use-case, I’d still like to compare concepts and architecture used under the hood of […]

Tech Talk Series

Vladimir Schreiner
by Vladimir Schreiner

Virtual meetups with Hazelcast covering data streaming and in-memory computing topics.

Don’t over-centralize your Kafka infrastructure

Vladimir Schreiner
by Vladimir Schreiner

This week, ThoughtWorks released its 18th edition of Technology Radar. As a product manager in a company which develops infrastructure software, I appreciate these overviews as they provide both technical and high-level insight. The current edition discusses Recreating ESB antipatterns with Kafka, something I have experienced personally. Going back in time to the early 2000s, […]

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