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.
Find out for yourself how to get a Hazelcast IMDG cluster up and running. In this Getting Started guide you’ll learn how to:
Learn how to run a distributed data stream processing pipeline in Java. In this Getting Started guide you’ll learn how to:
As a next step, you will be able explore the code samples and extend your setup more features and connectors.
Use Hazelcast IMDG to store your data in RAM, spread and replicate it across a cluster of machines, and perform data-local computation on it. Replication gives you resilience to failures of cluster nodes.
Use Hazelcast Jet to build data pipelines processing streams of events such as from message queues and database changelogs. The processing state is replicated, allowing you to scale up and down the computation without any loss of data.
Open-source distributed In-memory object store supporting a wide variety of data structures such as Map, Set, List, MultiMap, RingBuffer, HyperLogLog. Cloud and Kubernetes friendly.
Open-source distributed stream and batch processing with embedded in-memory storage and a variety of connectors such as Kafka, Amazon S3, Hadoop, JMS and JDBC.
Hazelcast provides tools for building distributed applications. Use Hazelcast IMDG for distributed coordination and in-memory data storage and Hazelcast Jet for building streaming data pipelines. Using Hazelcast allows developers to focus on solving problems rather than data plumbing.
It’s easy to get started with Hazelcast. The nodes automatically discover each other to form a cluster, both in a cloud environment and on your laptop. This is great for quick testing and simplifies deployment and maintenance. No additional dependencies.
Hazelcast automatically partitions and replicates data in the cluster and tolerates node failures. You can add new nodes to increase storage capacity immediately. You can use it as a cache or to store transactional state and perform data-local computations or queries. As all data is stored in memory, you can access it in sub-millisecond latencies. Clients for Java, Python, .NET, C++ and Go are available.
Use Hazelcast Jet to build massively parallel data pipelines. You can process data using a rich library of transforms such as windowing, joins and aggregations. Jet keeps processing data without loss even when a node fails, and as soon as you add another node, it starts sharing the computation load. First-class support for Apache Kafka, Hadoop and many other data sources and sinks.
Hazelcast has a full implementation of Raft, allowing a simple API for building linearizable distributed systems. Use tools like FencedLock, Semaphore and AtomicReference to simplify coordination between distributed applications.
Both Hazelcast Jet and Hazelcast IMDG are a single Java archive (JAR) less than 15MB. It’s lightweight enough to run on small devices, you can embed it into your application as just another dependency or deploy it as a standalone cluster. First-class support for Kubernetes is included.
Hazelcast is deployed in the most demanding environments and applications.
Redis and Hazelcast solve many similar use cases, most commonly caching. They are quite different in how they approach things such as cache patterns, clustering & querying.
Set up a Hazelcast cluster in Kubernetes, and make use of Hazelcast storage and messaging capabilities in your microservices architectures.
Use Hazelcast Jet to build a data processing pipeline that will process events from Apache Kafka as they arrive.
Use Hazelcast IMDG for storing and retrieving data from distributed in-memory data structures. You can store your data from one machine and access it from another or perform queries on it.
Cert-Manager became a standard way for issuing and rotating certificates in Kubernetes and OpenShift environments. Simple to install. Simple to use. Well integrated with Vault and other secret managers. No surprise it’s the way to go if you want to set up secure communication between your applications! In this blog post, I show how to […]
Virtual meetups with Hazelcast covering data streaming and in-memory computing topics.
Today is PI DAY! Obviously, Pi has rather more than 2 decimal places. To have some fun, let’s use Jet to drive multiple Python workers to calculate Pi with increasing accuracy. A tiny bit of mathematics Pi is the ratio of a circle’s radius to its circumference. It’s 3.14. It’s 3.1416. It’s 3.14159266 or whatever. It […]
Now, deploying Hazelcast-powered applications in a cloud-native way becomes even easier with the introduction of Hazelcast Cloud Enterprise, a fully-managed service built on the Enterprise edition of Hazelcast IMDG. Can't attend the live times? You should still register! We'll be sending out the recording after the webinar to all registrants.
Hazelcast Cloud Enterprise is the new cloud-native managed service that allows you to quickly set up Hazelcast IMDG in a public cloud, fully managed for you by Hazelcast. This tutorial will walk through deployment of Hazelcast Cloud Enterprise on Amazon AWS.
This short video explains why companies use Hazelcast for business-critical applications based on ultra-fast in-memory and/or stream processing technologies.
