Hazelcast Cloud is an enterprise-grade in-memory computing platform deployed and managed by the Hazelcast CloudOps team. The service
is powered by Hazelcast IMDG Enterprise HD and leverages widely adopted technologies, such as Docker and Kubernetes, to provide dynamic orchestration and containerization. Hazelcast Cloud supports applications developed in some of the most common languages, including Java, Node.js, Python. Go, and .NET.
Hazelcast Cloud delivers enterprise-grade Hazelcast software in the cloud, deployed as a fully managed service. Leveraging over a decade of experience and best practices, Hazelcast Cloud delivers a high-throughput, low-latency service that scales to your needs while remaining simple to deploy. If you’re considering moving to the Cloud, or are looking for an easy ramp on deploying in-memory technology, this white paper on migrating in-memory to the cloud is an informative and helpful resource.
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.
Join this webinar on April 11th at 8:00 am PT / 11:00 am ET / 4:00 pm GMT 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!
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When you need to pass boundaries of managed java environment, you find yourself playing (or fighting :) with C/C++ code (headers, compiler flags, linker flags ...).With version 1.5, Go is coming to save us, C/C++ is not your only option anymore...
Sending tasks or application logic to the data is a good step to achieve greater scalability, generally you need to inject some local dependencies into remote tasks before they are executed. In Hazelcast, there are a few ways of injecting dependencies into user objects. Spring Who doesn’t use Spring nowadays… If you are a Spring […]
JSR107, Java Temporary Caching API, also known as JCache is finally out after an effort of 13 years. It's like the only everlasting JSR of the JCP history. But long story short, it's completed now and companies in NoSQL/in-memory-data-grid/big-data world are competing each other to release their own implementations first.
While analysing application memory usage and inspecting allocation/garbage creation patterns, we generally need to know garbage collection count, time, rate etc. Although most of the profilers give this information out-of-the-box or JVM already has builtin flags to enable GC logging in many details, sometimes we want to access GC information programmatically.
Most probably you heard spurious wakeup term many times, you read it in many API docs. But have you actually seen it in the wild? Is it real?
To use JFreeChart in a Eclipse RCP project or simply embed in an SWT composite, you have two applicable choices: org.jfree.experimental.chart.swt.ChartComposite from JFreeChart SWT experimental project, which I can not say works seamless.
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.