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!
Payment processing networks and the ecosystems they drive are the foundation of the global economy. In this webinar, Hazelcast will present how in-memory technology enables the core drivers of both payment processing and the enablement of fraud detection applications, along with specific examples from global leaders in the banking, credit card, and e-commerce domains.
You’ll also get details on how a major bank was able to run multiple fraud detection algorithms at sub-millisecond speeds, how a major credit card provider can process millions of transactions per second while exceeding stringent SLA requirements, as well as how a major e-commerce player was able to reduce transaction processing times from minutes to seconds.
This is cutting-edge technology, applied to processes that billions of people (including you) are using continuously. To find out more about what in-memory technology can deliver, please click on the watch now button.
John DesJardins is currently Community Advocate and CTO for North America 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.