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!
Get a 30-day free trial.
Get started today with the
industry’s leading in-memory computing platform.
The in-memory speed you count on, with the convenience and scalability of cloud.
The first generation of microservices was envisioned as stateless request-response endpoints. But it’s now clear that microservices must often maintain some state. For example, microservices tasked with running machine learning models or engaged in statistical classification must maintain the state of their models and their parameter weights. This brings us to one of the biggest challenges—where is that state stored? Options like RDBMSs are too slow, do not scale, and have inflexible schema models. Distributed in-memory caching, however, is the only widely adopted enterprise technology that offers high speed, scalability, and dynamic schema evolution.
In this webinar, we will discuss:
Dale Kim is the senior director of technical solutions at Hazelcast and is responsible for product and go-to-market strategy for the in-memory computing platform. His background includes technical and management roles at IT companies in areas such as relational databases, search, content management, NoSQL, Hadoop/Spark, and big data analytics. Dale holds an MBA from Santa Clara, and a BA in computer science from Berkeley.
Lucas is a senior solutions architect at Hazelcast, where he helps Hazelcast’s most demanding customers architect, design, and operationalize enterprise software systems based around Hazelcast IMDG and Jet. Before joining Hazelcast, Lucas held similar positions at GigaSpaces and GridGain, giving him a uniquely broad and deep understanding of the in-memory platform space. Lucas holds a B.S.E. in computer science from the University of Michigan.