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.
Two years ago, when Forrester last published its Wave for Streaming Analytics, our streaming capabilities were still in the R&D phase. We were working on a technological challenge based on the belief there was a new generation of stream processing that was possible – one steeped in our ethos of defeating time. For the world […]
One of the features of Hazelcast Enterprise is the ability to share data between multiple Hazelcast clusters, whether geographically distant or adjacent. In this blog, we’ll look at the practicalities of keeping the data in multiple clusters synchronized. Business continuity wins There are two conflicting needs here. Data replication happens fastest the nearer the clusters […]
“Which serialization option is best?“. In this post we’ll explore some of the most common serialization options for Hazelcast, which includes standard coding, and the external libraries Avro, Kryo and Protobuf. Following our previous posts on how much memory you will need (here and here) which looked at object sizing in Java, we need to […]
No posts were found matching that criteria.
Where would you draw the line between a data store and a cache? Persistence? Hazelcast allows you to write your in-memory data on disk. Derived data vs. source of truth? If the cost of creating the data is cheap, why would you persist them? Let’s agree that there’s no clear-cut defining property but a blurry […]
This post was co-authored with Michal Biesek, a software engineer at Intel. It was originally published on the pmem.io blog as well. If interested in Persistent Memory development or PMDK in particular, check the other posts there, too. The mission of the PMDK team has always been and will always be to make programming persistent […]
I’m pleased to announce Management Center v4.2021.04 has been released as of today! Let’s see what this new release brings. Before we start, please note that the following features require you to have an enterprise license. You can request a free enterprise trial license here. Configuration Check Improvements Management Center has a very useful feature […]
The JDBC API was the first way to connect and execute queries on databases in Java and is still widely used today. To connect to a specific database, you add the relevant driver to the classpath which implements the JDBC API. On the other side, the application code only uses the SQL language: JDBC acts […]
Today we’re releasing Hazelcast Jet 4.5, the second release this year! We’re bringing Jet closer to IMDG, unifying their SQL syntax and features. Our goal is to have a single SQL dialect that seamlessly uses the features of both Jet and IMDG. This version of Jet is built on Hazelcast IMDG 4.2. Improved SQL Experience […]
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 […]
There are no more posts.
