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.
It is common to see many IT teams turn to caching technologies to speed up their access to data. This is perfectly valid, since caching accelerates applications by reducing the latency associated with retrieving data from a slower medium (i.e., a disk-based database) or from the farthest corners of your network.
The overarching business demands that caches fail to meet time and time again is the unification of data spread out across disparate systems and the analytical calculations needed to be performed on said data. This is the perfect opportunity to introduce a versatile technology that can come to the rescue: a digital integration hub (DIH), a data layer that not only stores data like a cache but also performs computations and aggregations of data so that other applications can access it in real time.
This paper explains why you should think beyond caching, and turn to more advanced, yet easy-to-integrate architectures like the DIH.