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!
Click to copy, then paste the following snippets into your build:
<name>Hazelcast Private Repository</name>
Pull hazelcast docker image from Docker registry via this command:
docker pull hazelcast/hazelcast-jet-enterprise
After that you should be able to run Hazelcast docker image by:
docker run -e JET_LICENSE_KEY=<your_license_key> -ti hazelcast/hazelcast-jet-enterprise
Install Hazelcast from the official Helm Chart via this command:
helm repo add hazelcast https://hazelcast.github.io/charts/
helm repo update
helm install --set image.tag=4.0 hazelcast/hazelcast-jet-enterprise
Hazelcast IMDG clients and programming language APIs allow you to extend the benefits of operational in-memory computing to applications in these languages. All of these clients and APIs are open source and all except the Scala client are supported by Hazelcast.