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.
IBM and Hazelcast deliver the most advanced solution for in-memory, in the cloud
Migrating applications where low latency is not a requirement is often the starting point for enterprise cloud migration strategies. There is, however, a general hesitation in migrating mission-critical and time-sensitive applications to the cloud when low latency is a high priority. This hesitancy is due to concerns around regional availability and inconsistent hardware from one cloud provider to another when employing a multi-cloud strategy.
To solve this problem, Hazelcast and IBM have announced a joint initiative to:
Mirroring the run-anywhere capabilities of the IBM Cloud Paks, the extremely lightweight footprint of the Hazelcast In-Memory Computing Platform enables it to be embedded or deployed alongside the application to shrink latency to microseconds. As cloud strategies evolve, it provides additional deployment flexibility for edge and microservices use cases.
Built on Kubernetes, the IBM Cloud Pak for Applications is one of five Cloud Paks designed to provide a faster, more secure way to move core business applications to any cloud environment through enterprise-ready containerized software.
For a growing number of Internet of Things (IoT) use cases, edge computing must be integrated with a cloud-based data center to address the challenges of capturing huge amounts of data from remote locations. However, deploying an edge computing solution has its own set of challenges, including limited computing space, security, and software change management. Hazelcast and IBM work together to drive edge-to-cloud solutions that are fast, efficient, lightweight, and secure. Connected cars, predictive maintenance on industrial equipment, and smart cities are just some examples where edge-to-cloud plays a key role.
Move and run WebSphere eXtreme Scale, OpenShift, Cloud Foundry, Cassandra, Kafka, and other high-performance workloads at scale onto ICP with Hazelcast, which delivers:
This solution brief describes how Hazelcast and IBM work together to deliver edge-to-cloud solutions that run the most innovative applications today.
It takes 300 milliseconds to blink. In that time a car has entered an intersection, a manufacturing robot has missed its mark, a video camera image has lost its usefulness. The digital era has created the new potential to innovate the world around us. In the process, it has also shrunk the concept of response […]
IBM customers working on application modernization projects from on-premises installations to cloud architectures will need the infrastructure to take advantage of cloud-native capabilities. However, customers using IBM eXtreme Scale on-premises will need an alternative in-memory technology, as eXtreme Scale does not support cloud environments using Kubernetes and containers. Read this paper to see how Hazelcast delivers in-memory speeds to applications built on IBM Cloud Paks.
