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!
Greg Luck is a leading technology entrepreneur with more than 15 years of experience in high-performance in-memory computing. He is the founder and inventor of Ehcache, a widely used open source Java distributed cache that was acquired by Software AG (Terracotta) in 2009, where he served as CTO. Prior to that, Greg was the Chief Architect at Australian start-up Wotif.com that went public on the Australian Stock Exchange (ASX:WTF) in 2006. Greg is a current member of the Java Community Process (JCP) Executive Committee, and since 2007 has been the Specification Lead for JSR 107 (Java Specification Requests) JCACHE. Greg has a master's degree in Information Technology from Queensland University of Technology and a Bachelor of Commerce from the University of Queensland.
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3.7 30% Faster Across the Board 3.7 EA just got released. And I am happy to say our Performance Team led by Peter Veentjer found another amazing optimisation. The main change this time was to remove notifyAll and synchronized blocks in the networking layer and replace them with LockSupport.park/unpark. The code change was done on […]
GridGain/Apache Ignite have released a benchmark which purports to show that they are faster than Hazelcast. This follows on from our Hazelcast/Ignite Benchmark using Yardstick, their own benchmark, which shows Hazelcast 3.6-EA was much faster than Ignite 1.4.1. In looking into it we discovered that they had faked the test. Instead of configuring the tests the […]
We got busy with performance at Hazelcast over the last year and a half. There are many different parts of the API to test. We have mostly been using competitors benchmarks to verify our performance increases. This week we wanted to find out how the versions had changed. So we did a performance test on […]
We should start calling Hazelcast, Hazelfast. Hazelcast 3.6 EA shipped last week, and it is very fast. Compared to what, you ask? Well, compared to everything. How do we know this? Well, our competitors made their own comparative benchmarking tools, YardStick … Continue reading →
Hazelcast has just released Hazelcast 3.5. From my point of view this is the best version we’ve ever created. Not only did we tighten our development process and increase QA efforts, it’s also the first version being tested in our new test-lab which Peter Veentjer loved to talk about a couple of weeks ago: […]
The times they are a changin’. We have noticed that our competitors have been changing their business models, open sourcing their cores and talking about building communities. For ourselves, we aren’t announcing any changes. And that’s the point. Hazelcast has a commitment to these issues which run deeper than business expediency. So, while we aren’t […]
We just released Hazelcast 3.2.2. This release is a stable, production-ready maintenance release. Stabilizer Testing This release was tested using our new production simulator, Hazelcast Stabilizer for 48 hours with the following configurations: small = [12 instance, memberWorkerCount … Continue reading →
We just released Hazelcast-3.3-EA with the following new features: Heartbeat for Java client filterless Tomcat 6&7 Web Sessions Clustering (Enterprise only) Enterprise WAN Replication (Enterprise only) Replicated Map Download Enterprise version here or open source version here. We anticipate the RC … Continue reading →
I am getting a few questions lately on JSR107 caching annotations and whether implementations of JSR107 are providing them. Caching annotations can be added to your Java classes and will invoke caching operations as the method. For example below is … Continue reading →
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