This short video explains why companies use Hazelcast for business-critical applications based on ultra-fast in-memory and/or stream processing technologies.
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.
Now, deploying Hazelcast-powered applications in a cloud-native way becomes even easier with the introduction of Hazelcast Cloud Enterprise, a fully-managed service built on the Enterprise edition of Hazelcast IMDG. Can't attend the live times? You should still register! We'll be sending out the recording after the webinar to all registrants.
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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The Java 9 EA version is out and we can now see how to use sun.misc.Unsafe. I led the public campaign to retain access to it in Java 9 which was ultimately successful, leading to the amendments to JEP 260. So, … Continue reading →
Today, we are thrilled to announce the availability of Hazelcast Striim Hot Cache. This joint solution with Hazelcast’s in-memory data grid uses Striim’s Change Data Capture to solve the cache consistency problem. With Hazelcast Striim Hot Cache, you can reduce the latency of propagation of data from your backend database into your Hazelcast cache to […]
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 →
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