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



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Delivering on the Internet’s Promise for Global E-Commerce Reach

Case Study

Credorax is a next-generation smart payments provider and fully licensed acquiring bank providing cross-border processing.

Accelerating Mobile Apps with In-Memory Technologies

Case Study

Swedbank is a large banking group based in Stockholm that uses in-memory computing to speed up systems driving mobile apps.

Fraud Detection with In-Memory Machine Learning

White Paper

This paper discusses the role of machine learning in fraud detection, and why improved fraud detection models are required today.

Continuous Query with Drill Down – Trade Monitoring Demo

| Video

The business use case we'll use for this demonstration is a Trade Monitoring application for middle-office and back-office teams in a capital markets trading firm.

Trade Monitoring for Risk and Compliance Solution Brief

| 2 pages

Back office analysts at capital market trading firms can now get on-demand, near-real-time summaries of the day’s trades.

Greater Trade Visibility in Capital Markets for Back-Office Functions

White Paper

The “cost versus risk” balance in capital markets trading firms can now be more efficiently addressed with modern technologies.

Hazelcast Continuous Query with Drilldown Trade Monitoring Reference Architecture

White Paper

Analysts in the back office of capital markets trading firms need greater visibility on trades throughout the day. This reference architecture paper describes the use of the Hazelcast In-Memory Computing Platform to cost-effectively enable a near-real-time stock trading analysis solution.

Hazelcast Continuous Query with Drilldown Trade Monitoring Technical White Paper

White Paper

Analysts in the back office of capital markets trading firms need greater visibility on trades throughout the day. This technical white paper describes a cost-effective solution that enables near-real-time querying on stock trading data.

Modern Platform for Always-On Digital Retail

| Video
| 60 minutes

Retail has become truly digital. Customers demand frictionless always-on experiences across all devices and all channels. Trends such as Touchless Retail and Buy-Online Pick-up Curbside or in-store are only accelerating in the current environment. At the same time, technologies such as Edge Computing, Machine Learning, and Augmented Reality are driving innovation and disruption. IBM, Intel, and Hazelcast are working together to deliver integrated solutions to meet these challenges.

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