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

Hazelcast Platform

Hazelcast platform is a distributed, highly available, cloud-native, in-memory data platform with unified user experience and management tooling. It is massively parallel and can process millions of operations per second with latencies in microseconds at scale. It is simple to use, no additional or third party coordination processes are required.

Overview

Cloud-native data & compute platform

Power your cloud-native applications with the world’s leading open-source in-memory data platform.

Hazelcast Platform Architecture

Powerful
Powerful

Hazelcast brings distributed data structures, processing, and coordination services in a light-weight package. Hazelcast services are carefully integrated so that you can compose them into powerful distributed applications.

Fast. Constantly.
Fast. Constantly.

Hazelcast can process millions of records per second, store Terabytes of data in-memory, and handle thousands of clients whilst maintaining microsecond access times. Hazelcast regularly proves itself to be a faster and more powerful option than NoSQL stores such as Redis, Cassandra or MongoDB.

Flexible
Flexible

Hazelcast clusters can add capacity and CPU by starting more member processes. The members can be added whilst the cluster is still running resulting in zero downtime. Data and computations are automatically rebalanced by the cluster to make use of all resources available.

Reliable
Reliable

Hazelcast provides safety by replicating data and computations across the cluster. Every member of the cluster is responsible for a portion of primary and replica entries. There is no concept of masters or replica processes. Hazelcast can intelligently place replicas on the safest member, on another physical machine or even another rack.

Integration
Integration

Extend Hazelcast with a rich set of plugins. Connect Hazelcast to a variety of systems including all major databases, storages and messaging systems [see all connectors]. Use the deployment kits for simple deployment to any cloud or container [see Cloud Discovery connectors]. Framework accelerators simplify using Hazelcast from Spring, Hibernate, web container or as a cache provider.

Unified Management
Unified Management

The Management Center enables monitoring and management of the Hazelcast cluster. This includes monitoring the overall state of clusters, resource utilization, running workloads as well as detailed analysis and browsing of data structures in real time, updating map configurations, and taking thread dumps from nodes.

Use Cases

Performance at scale

Application Scaling
Application Scaling

Hazelcast combines distributed data structures, distributed data processing, distributed coordination, elasticity, connectors and integration with Spring and Hibernate. These capabilities bring several benefits to enterprise deployments, including the ability to handle thousands of operations per second, prevent the loss of data after crashes, and dynamically scale as new servers are added.

Data Stream Processing
Data Stream Processing

A data stream is a series of isolated records. Make it queryable using Hazelcast. Cache recent values, correlate simple events with complex events, join streams or combine (aggregate) multiple values to build and maintain a queryable view of the streaming data. This reduces data access time for consumers and allows event-driven behavior.

Distributed Compute
Distributed Compute

Use Hazelcast to speed up your MapReduce, Spark, or custom Java data processing jobs. Load various data sets to a cluster cache and perform fast compute jobs on top of the cached data. You get significant performance gains by an combining in-memory approach with co-location of job and data and with parallel execution.

Caching
Caching

Hazelcast is one of the most popular open-source caching solutions, ensuring that data is in the right place when it’s needed for optimal performance.

Operational Memory
Operational Memory

Hazelcast is often used as an operational memory layer for databases in order to improve the performance of applications, to distribute data across servers, clusters and geographies, to ingest data at very high rates, and to manage large data sets.

Messaging
Messaging

Hazelcast has a broadcast messaging system offering a comparable set of features to JMS topics. Use Hazelcast messaging to glue Hazelcast services to powerful applications.

In-Memory NoSQL
In-Memory NoSQL

Hazelcast can function as an in-memory NoSQL key-value store. Increasingly, more and more deployments are seeing the advantages of ever-expanding RAM sizes at lower costs.

Microservices
Microservices

Package the embeddable and lightweight Hazelcast library and your application into a single container (such as Docker container or a Java JAR) to create self-contained data processing microservices.

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