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

Resources

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Hazelcast WAN Replication on Google Cloud Platform

Video
| Video

This video by Hazelcast senior solutions architect Sharath Sahadevan walks through a setup of WAN Replication on Google Cloud Platform.

Applied Machine Learning in Real-Time with Distributed, Scalable, In-Memory Technology

Webinar
| Video
| 60 minutes

Machine learning (ML) brings exciting new opportunities, but applying the technology in production workloads has been cumbersome, time consuming, and error prone. In parallel, data generation patterns have evolved, generating streams of discrete events that require high-speed processing at extremely low response latencies. Enabling these capabilities requires a scalable application of high-performance stream processing, distributed application of ML technology, and dynamically scalable hardware resources.

Cloud Native Scalable Rule Engine Demo

Video
| Video

See how the distributed compute features of Hazelcast can be used to build a rule engine for low-latency, high-throughput transaction processing.

Webinar

Turbo-Charge Your Applications from z/OS to Edge to Multi-Cloud with In-Memory Computing

December 2, 2020
2:00pm PST / 5:00pm EST / 10:00pm GMT

Mainframe computers are used at many companies today, but the need for more cost-effectiveness is forcing changes. A popular strategy, mainframe optimization, enables lower mainframe costs due to the reduction in unnecessary MIPS. At the same time, it adds powerful new architectures related to cloud, microservices, and data streaming. An integration with IBM and Hazelcast […]

Hazelcast In-Memory Computing Platform (IMCP) and Red Hat Data Grid (RHDG) Comparison

White Paper

Read why you should use Hazelcast over the Red Hat Data Grid for your application acceleration and architecture modernization initiatives.

Maintaining an Online Edge in Today’s Highly Competitive Banking World

Case Study

BNP Paribas S.A. is a French international banking group and one of the largest banks in the world by total assets.

Spring Data JPA and Hazelcast as Hibernate’s Second Level Cache

Video
| Video

Sr. engineer Grzegorz Piowawarek walks through the integration of Hazelcast as a Hibernate second level cache within Spring Boot

Quarkus and Hazelcast Client Extension

Video
| Video

Sr. engineer Grzegorz Piowawarek walks through the integration of Hazelcast into a Quarkus application.

From Edge to Cloud: Boosting Data-Driven Business Performance in Times of Uncertainty

Webinar
| Video
| 60 minutes

Join Hazelcast and Intel for this deep dive into how your organization can create a single, unified data plane that extends all the way from the myriad things at the edge of your business right into your corporate cloud or data center.

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