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.
Building containerized software that runs on Kubernetes platforms like Red Hat OpenShift Cloud Platform is the hot trend in software development. Everyone is building containers, but the technology is new enough that best practices and certifications are still being developed. IBM specializes in providing software for enterprises. An example of this software is IBM Cloud […]
This blog shows you how you can install Hazelcast on Azure Kubernetes Service (AKS) and connect to the cluster using an Hazelcast client. It assumes some familiarity with Kubernetes , Azure and Azure Cloud shell. The goal of this blog is to keep things simple and show you the steps to get up and running […]
“How Jet compares to Spark” and “why should I choose Jet over Spark” are arguably the most frequent questions I’ve been asked during the talks and workshops. While it is hard to assess the product fit without focusing on a concrete use-case, I’d still like to compare concepts and architecture used under the hood of […]
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We are happy to present the new release of Hazelcast Jet 4.1. Here’s a quick overview of the new features. Extended gRPC Support We’ve applied the lessons learned from the Jet-Python integration and made it easier to integrate a Jet pipeline with gRPC services. The utility class GrpcServices introduces two new ServiceFactorys you can use with the mapUsingServiceAsync transform. Using this feature […]
It takes 300 milliseconds to blink. In that time a car has entered an intersection, a manufacturing robot has missed its mark, a video camera image has lost its usefulness. The digital era has created the new potential to innovate the world around us. In the process, it has also shrunk the concept of response […]
Why? Our blog already contains numerous articles about running Hazelcast in containers, but they mainly focus on orchestrated platforms (Kubernetes, ECS, GCP, …). According to a 2018 Docker adoption report, half of the deployments did run in non-orchestrated environments 2 years ago. I didn’t find a similar report from 2020, but I expect the proportion […]
Once one starts their journey in data streaming, one starts to discover a lot of applications beyond just the standard Extract-Transform-Load pattern. The traditional model to deliver a new version of a Java application is to stop the process, deploy the new JAR/WAR, and start the process again. This directly results in downtime: in this […]
Spring Boot is a framework that helps to build microservices easily. In the Java ecosystem, it’s one of the most preferred ways of building microservices as of now. In a microservice architecture, there are different options to share data among the running services: one of them is caching, which Spring Boot leverages. It also provides […]
As we have announced earlier, Jet 4.0 is out! In this blog post, we aim to give you the lower-level details needed for migrating from older versions. Jet 4.0 is a major version release. According to the semantic versioning, we apply, this means that in version 4.0 some of the API has changed in a […]
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