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!
Today, we’re happy to announce the general availability of Hazelcast Cloud Enterprise on AWS. This much-anticipated release will make it even easier for solution architects and developers with a need for extra-low latency to leverage the power of Hazelcast IMDG within their cloud technology stack. What is Hazelcast Cloud Enterprise? Even though we already offer […]
Hazelcast Cloud Enterprise is the new cloud-native managed service that allows you to quickly set up a cluster of Hazelcast IMDG nodes in a public cloud (Amazon Web Services today, with Google GCP and Microsoft Azure coming later this year), and have that cluster fully managed for you by Hazelcast. Setting up the cluster requires […]
Hazelcast Jet is a distributed stream processing engine that supports exactly-once semantics even in the presence of cluster member failures. This is achieved by snapshotting the internal state of the processors at regular intervals into reliable storage and then, in case of a failure, using the latest snapshot to restore the state and continue. However, […]
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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 […]
I joined Hazelcast in January 2014 as employee number 12. At that time Hazelcast 3.1 was the current version. Since then, about every 7-8 months we have done a “minor” release, the latest of which is 3.12. Minor in the sense that they maintained binary compatibility. We added many features and improved many aspects of […]
Today, Hazelcast is moving to a three-license software licensing model: Apache 2.0 for the core of our systems, consistent with our history A new source-available Hazelcast Community License A proprietary license for selected Enterprise operational features, consistent with our history The license model change will have no impact on users and is only intended to […]
Hazelcast loves Kubernetes. Thanks to the dedicated Hazelcast Kubernetes plugin, you can use dynamic auto-discovery. Hazelcast on Kubernetes can also run in multiple topologies: embedded, client-server, or as a sidecar. What’s more, thanks to the Helm package manager and the dedicated Hazelcast Helm Chart, you can deploy a fully functional Hazelcast server in literary minutes. […]
Let’s start off the New Year with a fun code example! This example shows how Jet is used to spot the dramatically-named Death Cross for the price of Bitcoin, which is an indication to sell, Sell, SELL!. The idea here is that we could automatically analyze stock market prices and use this information to guide […]
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 […]
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