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!
Istio is said to be the next thing if you follow the Kubernetes path, and service meshes are mentioned whenever you go to a cloud-native meetup or conference like KubeCon. However, you do not always leverage something for the sake of popularity. The Hazelcast-Istio support discussion was started by a user after a GitHub issue […]
Data is valuable. Or I should write, some data is valuable. You may think that if the data is important to you, then you must store it in the persistent volume, like a database or filesystem. This sentence is obviously true. However, there are many use cases in which you don’t want to sacrifice the […]
Hazelcast Jet 3.2 introduces stateful map, filter, and flatmap operations, which are very strong primitives. In this blog, I am going to show you how to use stateful filter for detecting and removing duplicate elements in a stream. Why Deduplication? Deduplication is often used to achieve idempotency or effectively-once delivery semantics in messaging systems. Imagine […]
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 […]
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We are excited to announce the new repository for extension modules of Hazelcast Jet. This repository will be home for the Hazelcast Jet extension modules, including connectors (including both sources and sinks), custom aggregations, and context factories. All of these modules will help make the integration easier for 3rd-party products in your pipelines. The main […]
Stream processing refers to real-time management of data entering a banking system (or any information system, actually) at high speed and volume, usually from a broad range of sources. The “management” aspect means data is wholly or partially processed and contextualized before entering an in-memory (operational) system, where pre-processing can significantly accelerate response times. Before […]
After releasing Hazelcast Jet 3.0 in May, we are happy to announce its first update, Hazelcast Jet 3.1. Hazelcast Jet is now an Apache Beam Runner Apache Beam is a framework for building distributed batch and stream processing applications over a unified API. The API itself is decoupled from the underlying execution implementation, making it […]
Unbounded, unordered, global-scale datasets are increasingly common in day-to-day business – IoT sensor network data streams, mobile usage statistics, large scale monitoring, the list is endless. Numerous applications seek the ability to quickly react to dynamic streaming data, as it is either a mandatory requirement or a competitive advantage. API Churn As a consequence, lots […]
Hazelcast IMDG is tightly integrated into the Kubernetes ecosystem thanks to the Hazelcast Kubernetes plugin. In previous blog posts, we shared how to use auto-discovery for the embedded Hazelcast and steps for scaling it up and down using native kubectl commands. In this post, we’ll focus on another useful feature, Rolling Upgrade. You can apply […]
The megatrends that have been driving the adoption of Hazelcast by the world’s largest organizations are now strikingly clear: Enterprises are awash in data and must leverage it for business advantage New applications must process stored and streaming data Application latency is the new downtime. The money is in the microseconds To meet these needs […]
At Hazelcast we take reliability very seriously. With the new CP Subsystem module, Hazelcast has become the first and only IMDG that offers a linearizable distributed implementation of the Java concurrency primitives backed by the Raft consensus algorithm. In addition to well-grounded designs and proven algorithms, reliability also requires a substantial amount of testing. We […]
The sidecar pattern is a technique of attaching an additional container to the main parent container so that both would share the same lifecycle and the same resources. You may think of it as a perfect tool for decomposing your application into reusable modules, in which each part is written in a different technology or […]
Last week, Hazelcast earned a coveted spot on the list of Red Herring’s Top 100 North America private technology companies. Make no mistake, there was nothing fishy or misleading about this honor. Ok, enough of the “red herring” puns. If you’re not familiar with Red Herring, it is a global media organization aimed at uniting […]
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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.