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.
If you build Spring Boot applications that use Hibernate as your Spring Data Java Persistence API (JPA), you likely want to add a second level cache to provide faster access to frequently used data objects. With Hazelcast, you can get that faster access in a shared distributed cache that is available to all application instances, and not limited to each specific instance.
In this video, Hazelcast senior software engineer Grzegorz Piwowarek walks you through the steps to integrate Hazelcast into a Spring Boot application that leverages the Spring Data JPA using Hibernate.