Get Started

Get Started

These guides demonstrate the operational flexibility and speed of the Hazelcast In-Memory Computing Platform. Set-up in seconds, data in microseconds. Operations and developer friendly.

Hazelcast IMDG

Find out for yourself how to get a Hazelcast IMDG cluster up and running. In this Getting Started guide you’ll learn how to:

  • Create a Cluster of 3 Members.
  • Start the 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 the automatic rebalancing of data and back-ups.

Hazelcast Jet

Learn how to run a distributed data stream processing pipeline in Java. In this Getting Started guide you’ll learn how to:

  • Start a Hazelcast Jet cluster in your JVM.
  • Build the Word Count application.
  • Execute the application wit Jet.
  • Push testing data to the cluster and explore results

As a next step, you will be able explore the code samples and extend your setup more features and connectors.

About the Author

Nicolas Frankel

Nicolas Frankel

Developer Advocate, Hazelcast

Nicolas Fränkel is a Developer Advocate with 15+ years experience consulting for many different customers, in a wide range of contexts (such as telecoms, banking, insurances, large retail and public sector). Usually working on Java/Java EE and Spring technologies, but with focused interests like Rich Internet Applications, Testing, CI/CD and DevOps. Currently working for Hazelcast. Also double as a teacher in universities and higher education schools, a trainer and triples as a book author.

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An Easy Performance Improvement with EntryProcessor

Nicolas Frankel
by Nicolas Frankel

A lot of a developer’s work is about transforming and aggregating data: Increasing the quantity of a product in a shopping cart Applying VAT on the price of a product Computing the price of a shopping cart Etc… Sometimes, one needs the features of a full-fledged stream processing engine, such as Hazelcast Jet, sometimes not. […]

Persisting In-Memory Data for Later Usage

Nicolas Frankel
by Nicolas Frankel

Among the many capabilities of an in-memory data grid (IMDG), caching is one of the most well-known and used. However, as its name implies, data resides in memory. The memory is of finite capacity. In order not to put more data than memory can handle, we must decide how to curate it. Hazelcast comes with […]

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