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

Virtual Meetup: Machine Learning at Scale Using Distributed Stream Processing

Live Event

August 20, 2020 @ 6:00pm EDT

There is frequently an “impedance mismatch” between developing and training a machine learning module (a data scientist’s job) and then making that model deploy and perform at scale in a production environment (a data engineer’s job). How do you make a trained prediction model usable in real-time, while the user is interacting with your software? What does it take to go from fast trial-and-error runs on historical data to models that perform at production scale, in real-time?

In this talk we will demonstrate a practical approach that allows you to write a low-latency, auto-parallelized, and distributed stream processing pipeline (Java), using a model developed in Python.

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