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.
Multi-cloud strategy has become a new norm in application deployments, and for good reasons – redundancy and vendor lock-in concerns, along with business and technical goals. That’s why you need technologies that simplify the effort in maintaining a multi-cloud architecture.
Hazelcast adds in-memory speeds to your applications and includes capabilities that allow running multiple clusters on different IaaS and PaaS systems while ensuring data across all clusters remains consistent and in sync. This guide discusses one such example of a multi-cloud deployment with Hazelcast and Red Hat OpenShift.
The accompanying video is available here.