Distributed Data Processing and Storage with Hazelcast Training Course


Hazelcast is an open source in-memory data grid platform for distributed computing and data storage. It provides a scalable cluster for efficient workload handling and integration with data sources and cloud technologies.

This instructor-led, live training (online or onsite) is aimed at developers and system administrators who wish to use Hazelcast for processing distributed data structures and optimizing application performance.

By the end of this training, participants will be able to:

  • Install and configure Hazelcast to start creating and managing a cluster.
  • Create a cluster for initiating automatic discovery of multiple processes.
  • Set up Management Center for cluster connections and monitoring.
  • Develop applications and deploy them through the Hazelcast cluster.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.


  • An understanding of distributed systems
  • Experience with in-memory database technologies
  • Java programming experience


  • Developers
  • System administrators

Course Outline


  • Hazelcast vs Redis
  • Overview of Hazelcast Features and Architecture
  • Understanding distributed data structures

Getting Started

  • Installing and configure Hazelcast
  • Creating and starting a cluster

Exploring Hazelcast Tools

  • Caching data
  • Implementing data ingestion
  • Running distributed queries

Working with Data Streams

  • Building data pipelines
  • Transforming data streams
  • Aggregating stateful data

Testing Hazelcast Clusters

  • Running integration tests
  • Randomizing cluster names
  • Cleaning up and testing sources

Managing Clusters

  • Securing a cluster
  • Monitoring and maintaining a cluster
  • Optimizing cluster performance
  • Deploying applications on premise and cloud environments


Summary and Next Steps

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