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!
Get a 30-day free trial.
Get started today with the
industry’s leading in-memory computing platform.
The in-memory speed you count on, with the convenience and scalability of cloud.
Table of Contents
Overall RadarGun configuration
Zing reduces full GC pauses.
So we would expect this to reflect in average latencies and, because larger full GCs are avoided,
much more so in the largest max latencies. And this is what we found.
The average was reduced by 40%. The 99.99th percentile max latency was only 8ms for Zing
but 55ms for HotSpot.
We conclude that Hazelcast® with Azul Zing JVM has lower latency and much lower variability
for more predictable latencies. This in turn allows Hazelcast to fit into tighter response time SLAs.
These results are applicable to small heap sizes where Hazelcast is storing small amounts of data of 500MB to 1.5Gb
per node and are relevant to Hazelcast and Hazelcast Enterprise.
Note that in Hazelcast Enterprise HD, we store data off heap and only run with a small heap.
So a similar benefit to one in these tests with 1 to 2GB heaps would be realized.
See below for summaries of results for 1GB and 2GB heap cases and the extensive test results further down.
Average response time for Get of 0.8ms versus for Get of .5ms for Zing
Max response for 99th percentile for Get of 2ms compared to 2ms for Zing
Max response for 99.99th percentile for Get of 40ms compared to 8ms for Zing
Max response for 99.99th percentile for Get of 55ms compared to 8ms for Zing