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.
Nicolas Fränkel is a Developer Advocate with 15+ years experience consulting for many different customers, in a wide range of contexts (such as telecoms, banking, insurances, large retail and public sector). Usually working on Java/Java EE and Spring technologies, but with focused interests like Rich Internet Applications, Testing, CI/CD and DevOps. Currently working for Hazelcast. Also double as a teacher in universities and higher education schools, a trainer and triples as a book author.
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Since we announced the nomination of Tomasz Gawęda, a new Hero has popped up. We are very happy to officially nominate Lenny Primak from the USA to be our latest Hero in the program. Lenny is a long-time contributor, but some of the Pull Requests he made couldn’t be merged by our teams in a […]
We recently announced our Hazelcast Heroes program to recognize the efforts of the most engaged contributors in our community. Today, we are very excited to announce our newest Hero, Tomasz Gawęda from Poland! Tomasz became a Hero by having five of his Pull Requests merged. He was kind enough to answer our questions regarding his […]
When your application starts slowing down, the reason is probably a bottleneck somewhere in the execution chain. Sometimes, this bottleneck is due to a bug. Sometimes, somebody didn’t set up the optimal configuration. And sometimes, the process of fetching the data is the bottleneck. One option would be to change your whole architecture. Before moving […]
Hazelcast is built on open source foundations. It’s part of our DNA, and we strive to uphold open source values in our day-to-day work. This commitment allows external contributors to make Hazelcast better so that the whole community can benefit from a collective effort. No contribution is too small, but, indeed, some of our community […]
At Hazelcast, open source is not only a business model; it’s the foundation of our company. We believe in the right of users to access, read, and improve upon our work. Because we know that it’s not easy to get started in open source in general, especially within a specific project, we participated in this […]
From Wikipedia, Reactive Programming is “a declarative programming paradigm concerned with data streams and the propagation of change.” The programming model is complex to master. It requires a lot of experience to feel comfortable with it. However, there’s no denying that it fits the cloud ecosystem perfectly. Since on-premises infrastructure is oversized, running a program […]
Google Summer of Code (GSoC) is a summer initiative that allows students to obtain a first deep dive into Open Source projects. It has several benefits: GSoC creates bonds between students and Open Source communities. Some, but not all, students continue to contribute to the Open Source project they worked on after GSoC This initiative […]
It has been said that there are two things hard in software development, naming things and cache invalidation (while some add off-by-one errors to the mix). I believe that keeping the cache in sync with the source of truth might count as a third one. In this post, I’d like to tackle this issue, describe […]
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 […]
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