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.
No posts were found matching that criteria.
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 […]
Hazelcast Jet allows you to distribute stream processing over several cluster nodes. While it comes with several out-of-the-box sources to read from (Hazelcast IMap, JMS, JDBC, etc.), and sinks to write to, there’s no Java 8 streams source. In this post, we are going to create an adapter to bridge this gap. A Look at […]
A lot of a developer’s work is about transforming and aggregating data: Increasing the quantity of a product in a shopping cart Applying VAT on the price of a product Computing the price of a shopping cart Etc… Sometimes, one needs the features of a full-fledged stream processing engine, such as Hazelcast Jet, sometimes not. […]
Among the many capabilities of an in-memory data grid (IMDG), caching is one of the most well-known and used. However, as its name implies, data resides in memory. The memory is of finite capacity. In order not to put more data than memory can handle, we must decide how to curate it. Hazelcast comes with […]
There are no more posts.