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!
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industry’s leading in-memory computing platform.
The in-memory speed you count on, with the convenience and scalability of cloud.
Risk is currently the driver of many development efforts in the finance industry. When developing financial risk systems you are faced with a number of challenges such as implementation and distribution of complex algorithms, Big Data, class modelling and UX design. Selecting the right technology can help you tremendously and simplify your architectures. Hazelcast® forms the foundation of Sungard’s risk product offering and delivers significant benefits to us in a number of areas. The open architecture allows us to understand and find the optimal solutions to the challenges we are up against.
This webinar aims to give you an overview of our main use cases and how Hazelcast helped us to deliver award-winning risk systems to some of the biggest financial institutions in the world. We will demonstrate how it is used as the execution engine in our analytics grid, our Portable implementation of our security master and market data repository and how we integrate it with Node.js.