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.
This reference implementation whitepaper discusses the implementation details behind the use of Hazelcast as a cloud-native foundation (public or private) for a cost-effective, “straight-through-processing” credit value adjustment risk calculation system. A combination of in-memory storage, stream processing, and distributed computing serves as a model for a large-scale calculation that involves tens of thousands of CPU cores.
Financial services firms looking to reduce cost while adding capabilities and agility to their risk calculation processes should explore this paper to see how Hazelcast can help.
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