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!
Are you ready to take your algorithms to the next steps and get them working on real-world data in real-time? We will walk through an architecture for taking a machine learning model into deployment for inference within an open source platform designed for extremely high throughput and low latency.
We’ll demonstrate a working example of a machine learning model being used on streaming data within the Hazelcast In-Memory Computing Platform, a powerful technology for distributed in-memory processing. We will also touch on important considerations to ensure maximum flexibility for deployments that need the flexibility to run either on-premises or in the cloud.
Scott McMahon is a Senior Solutions Architect at Hazelcast® with over 20 years of software development and enterprises consulting experience. Before specializing in Hazelcast In Memory Data Grid technology he built big data analytics platforms and business process management systems for many of the worlds leading corporations. He currently lives in Portland, Oregon, and when not working on computer systems, he enjoys getting outdoors and having fun with his family.