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.
Marko Topolnik, PhD, has been a Java professional since 2001. His current position is in the core team of Hazelcast Jet, where he co-wrote the core execution engine based on coroutine-like suspendable code that runs many concurrent tasks on a fixed thread pool. Marko is also an active contributor on Stack Overflow on the kotlin-coroutines tag.
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Today we’re releasing Hazelcast Jet 4.5, the second release this year! We’re bringing Jet closer to IMDG, unifying their SQL syntax and features. Our goal is to have a single SQL dialect that seamlessly uses the features of both Jet and IMDG. This version of Jet is built on Hazelcast IMDG 4.2. Improved SQL Experience […]
We’re currently preparing a scientific paper on Hazelcast Jet, describing its architecture based on symmetric, data-local, non-blocking distributed event processing. As part of this effort, we implemented the vendor-neutral NEXMark benchmark suite, consisting of 8 streaming queries that aim to capture typical kinds of questions you’re likely to ask about your real-time data. The queries deal […]
Today we’re releasing Hazelcast Jet 4.4 and we have some exciting new features! Jet SQL Hazelcast Jet 4.4 brings you the first beta version of our SQL interface. You can now log into Jet from the command line and issue queries against the data sources you specify. They can be both data at rest (batch sources) […]
Today we’re releasing Hazelcast Jet 4.3, our fourth release of 2020! We took part in Google Summer of Code that ended just a few weeks ago, and this release already brings a production-ready piece of work by our student, Mohamed Mandouh: distributed in-memory sorting. Mohamed’s primary focus was research into the feasibility of integrating RocksDB […]
In Hazelcast Jet 0.7 you have several options to enrich your data stream, varying in simplicity, flexibility and performance characteristics. This article shows you how to pick the right one. What is Data Enrichment The main purpose of Hazelcast Jet is to process infinite distributed streams of events. An almost universal first processing step is […]
