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.
There are common themes when people describe their reasons for rearchitecting legacy business applications, at a technical level: Speed & Scalability. At a business level: The need to gain new insights flowing from an increasing stream of data. These legacy applications commonly centre around some central datastore such as a relational database. Moving away from this architecture requires massive migration effort. The costs and risks associated with such an effort can sometimes be prohibitive for business owners, you can’t just rip out your relational database.
A lower risk, gradual transition to a target architecture often wins the day. It turns out that Streaming, Caching & CDC technologies are vital tools for this journey. CDC (Change Data Capture) can turn your legacy data stores into streaming sources. Modern caching technologies can host data in a way that provides speed and scalability, and finally streaming acts as the glue that can drive new uses cases as well as bridging the old.
By the end of this talk, you’ll understand how to employ these technologies (with concrete examples and demos) over a legacy architecture and also be able to reason about the trade-offs involved.