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.
Mainframe computers are used at many companies today, but the need for more cost-effectiveness is forcing changes. A popular strategy, mainframe optimization, balances mainframe usage with in-memory computing closer to the application tier, reducing unnecessary MIPS. At the same time, it adds powerful new architectures related to cloud, microservices, and data streaming.
An integration with IBM and Hazelcast can provide a seamless fast data and compute plane that runs anywhere from z/OS, to edge, to multi-cloud, accelerating your applications. With microservices, serverless, and cloud-native applications, you can seamlessly interact with your core business systems running on z/OS. And you retain the same always-on zero downtime service levels you have come to expect from the Z Platform.
In this webinar, we will discuss new capabilities for your mainframe-centric environment, and also show a demonstration running across z/OS, and OpenShift in IBM Cloud.
John DesJardins is currently CTO at Hazelcast, where he is championing the growth of our Developer and Customer Community. His expertise in large scale computing spans Data Grids, Microservices, Cloud, Big Data, Internet of Things, and Machine Learning. He is an active blogger and speaker. John brings over 20 years of experience in architecting and implementing global scale computing solutions, including working with top Global 2000 companies while at Hazelcast, Cloudera, Software AG and webMethods. He holds a BS in Economics from George Mason University, where he first built predictive models, long before that was considered cool.
Francesco is a Solutions Architect with Hazelcast, where he works as a member of the Support team, always striving to provide the best possible service to our valued customers. Prior to joining Hazelcast, Francesco worked for many companies, primarily operating in the financial, resources and IT industry, in roles such as systems programming, systems administration, and software engineering. He holds a Laurea in Mathematics from the University of Parma, Italy. Francesco is currently based in Brisbane, Australia.