Companies need a data-processing solution that increases the speed of business agility, not one that is complicated by too many technology requirements. This requires a system that delivers continuous/real-time data-processing capabilities for the new business reality.
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.
Setting up servers and configuring software can get in the way of the problems you are trying to solve. With Hazelcast Cloud we take all of those pain points away.
Watch this webinar to learn how you can instantly fire up and then work with Hazelcast Cloud from anywhere in the world. With our auto-generated client stubs for Java, Go, Node.js, Python and .NET, we can have you connected and coding in less than a minute!
We are excited to announce that Hazelcast in-memory technologies are now available for sale from IBM with the IBM Cloud Pak™ for Applications. The Hazelcast in-memory computing platform is an ultra-fast processing architecture for mission-critical applications where microseconds matter. The world’s most data-centric companies complement their systems of record, such as databases, with in-memory solutions […]
It is my pleasure to announce that after 6 years a new major version of Hazelcast has been released! This new release brings a breath of fresh air into Hazelcast while also being more robust than ever. We did try to keep enough familiarity to not surprise our users too much, but we also invested […]
If you had a choice of processing data in-memory versus not in-memory, all other things being equal, wouldn’t you always choose in-memory? You might not need the higher performance, but if it were available to you, you’d take it because faster is always better than slower, right? It would be wonderful if we lived in […]
Cloud technologies give you on-demand options so that you can create compute, disk, or network resources based on your requirements. When your demand changes, you update the infrastructure by releasing some resources or adding more. That is actually named “manual scaling” which is based on human intervention. Kubernetes is no different in this particular use […]
We are excited to introduce Hazelcast Jet 3.2, the latest version of Hazelcast’s batch and stream processing platform. We’ve added a number of powerful capabilities that not only expands the addressable use cases, but also further simplifies your application development efforts. Stateful Mapping Operator Jet now has support for more general fault-tolerant, stateful operations that […]
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UPDATE (9/4/19): I posted a new blog that showcases how we believe Redis achieves the performance in its benchmarks. Due to its underlying architecture and many years of optimization, Hazelcast is extremely fast and dramatically outperforms Redis Labs (and Redis open source), especially at scale. Last year, Redis Labs published a very misleading benchmark against […]
Hazelcast IMDG supports auto-discovery for many different environments. Since we introduced the generic discovery SPI, a lot of plugins were developed so you can use Hazelcast seamlessly on Kubernetes, AWS, Azure, GCP, and more. Should you need a custom plugin, you are also able to create your own. If your infrastructure is not based on […]
Another massive, transformative technology wave is about to hit, and while this won’t be quite as overt as some of the other waves (e.g., mobility, social media), its effect will be much more pervasive and will hit every consumer, business and industry on multiple levels. The next generation of mobile infrastructure, 5G, is in the […]
Hazelcast Jet is known for its high-performance and this is partially due to it employing green threads. This approach avoids the need for operating system threads, which are expensive to switch. Instead, task switching is performed by the application code in a lightweight way. What are green threads? With “normal” threads, you ask the OS […]
We are happy to announce the first General Availability release of Hazelcast Jet, two years after our first public release and three years after the project first started. We named this version 3.0 to match the current major version of Hazelcast IMDG, which is the underlying technology used in Jet. This version also includes several […]
We are pleased to announce the production-ready release of Hazelcast IMDG 3.12. We’ve crushed a lot of bugs, provided general performance improvements, plus we’ve added some great new features (more of which below). The release by numbers: 676 Issues 784 Pull Requests 47 Committers 168 Days Elapsed CP Subsystem The new CP Subsystem provides implementations […]
There’s a trio of buzzwords that are starting to spend more time in proximity to each other, and are also beginning to surface from the technical to the business world. Each by itself is critical, and when you combine all three, the business-level effect becomes very noticeable. These buzzwords and the business descriptors are: Kubernetes: […]
“Distributed locks aren’t real”, some like to remind us. “Anyone who’s trying to sell you a distributed lock is selling you sawdust and lies.” This may sound rather bleak, but it doesn’t say that locking itself is impossible in a distributed system: it’s just that all of the system’s components must participate in the protocol. […]
Today, we are announcing the general availability of Hazelcast Cloud, our new managed service. I remember the day about 9-years-ago when I created my first cluster in Hazelcast and how impressed I was by the ease of the process and the limited need for configuration. A year later, I joined the company as a developer, […]
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Whether you're interested in learning the basics of in-memory systems, or you're looking for advanced, real-world production examples and best practices, we've got you covered.