This short video explains why companies use Hazelcast for business-critical applications based on ultra-fast in-memory and/or stream processing technologies.
Stream processing is a hot topic right now, especially for any organization looking to provide insights faster. But what does it mean for users of Java applications, microservices, and in-memory computing? In this webinar, we will cover the evolution of stream processing and in-memory related to big data technologies and why it is the logical next step for in-memory processing projects.
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.
Java developers are particularly spoiled when using Hazelcast. Because Hazelcast is developed in Java, it’s available as a JAR, and we can integrate it as a library in our application. Just add it to the application’s classpath, start a node, and we’re good to go. However, I believe that once you start relying on Hazelcast […]
“How much memory do I need for my data?“. — continued! In an earlier post, the space needed to store basic data, such as numbers, was examined. However, we deferred the discussion related to more complex data structures, like the example below: Person { String firstName; String lastName; int age; } At the time, we […]
It’s a pleasure to announce the general availability of Hazelcast IMDG 4.2! In this blog post, we highlight the most notable features and enhancements in this release. We resolved almost 150 GitHub issues and merged roughly 350 pull requests and you can find the complete list of changes in the release notes. Don’t hesitate to […]
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Contract-first development is a methodology where we first create a design document (or interface definition) that formally describes the REST API we are going to implement, before writing any actual prototype. This methodology is useful for clearly communicating the structure and capabilities of the upcoming API before we implement it. Given a formal description of […]
We’re currently preparing a scientific paper on Hazelcast Jet, describing its architecture based on symmetric, data-local, non-blocking distributed event processing. As part of this effort, we implemented the vendor-neutral NEXMark benchmark suite, consisting of 8 streaming queries that aim to capture typical kinds of questions you’re likely to ask about your real-time data. The queries deal […]
Please forget the pun in the post’s title, I couldn’t resist. Today, we are happy to welcome another Hero from our community, Piotr Jasina. In this post, I asked my usual battery of questions to Piotr. Nicolas Fränkel: Hello Piotr! Congratulations on being promoted to Hazelcast Hero! It’s a pleasure to interview you. Let’s start […]
The Hazelcast .NET Client, version 4.0, is now available! This is a major release with important changes which aim at making the Hazelcast Client a true native .NET client. Where version 3.x of the client often showed its Java origins, version 4.0 has been refactored from the ground up to fully embrace the .NET ecosystem, […]
Today, I’d like to offer an approach that will allow most organizations to proceed with zero-downtime deployments with help from the Hazelcast platform. Applications are not stateless! A couple of years ago, I became interested in Continuous Deployment as the natural extension of my deep interest in Continuous Integration. Among the CD patterns, Blue-Green deployment […]
In a previous blog post, Designing an Evergreen Cache with Change Data Capture, Nicolas describes “one-way” change data capture (CDC). It is a one-way process. In Nicolas’ post, the database copy can change and CDC pushes the change to Hazelcast to align the two copies of the data. Let’s take this a stage further, with “two-way” […]
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