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.
Hazelcast’s low latency in-memory computing platform is ideal for AIOps applications.
Fast Stream Processing for data filtering and aggregation – many IT Ops tools charge for the data stored. Hazelcast Jet enables you to sample/filter/aggregate data ingested into AIOps and ITOps tools, helping reduce costs while still delivering real-time visibility.
Ultra-Fast Distributed Machine Learning – Bring the machine learning closer to applications across Multi-Cloud and Edge Architectures to drive further autonomous sense and response capabilities.
Edge-to-Cloud Ingest – Hazelcast Platform can run at the Edge, where the volumes of data are orders of magnitude greater, and therefore it isn’t practical to bring all the data back and aggregation, filtering, sampling and compression become a necessity.
Ingest and Correlation Z/OS to Multi-Cloud and Microservices – Today’s complex applications are interconnected, requiring cross-platform visibility to correlate problems across omni-channel applications in microservices and Core applications running on Z Platform. End-to-end visibility plus AIOps ensures accurate, fast root cause analysis and a complete picture of business impacts.
Hazelcast can be run at the edge, in any cloud (private, hybrid or multi-) to run and accelerate AIOps applications that need to process and analyze critical operations to create efficiency on technology deployments.
In the modern world what makes the difference is the shelf-life of your data analysis. When you run analysis on your data to derive insights, these insights rely on the recency of the data. All you need is a stream processing engine integrated with a fast data store. Changes in core data in the data store flow through streaming analytics to create derived data. If it’s all integrated, performance is excellent for high volume and low latency.
A global bank rolled out a highly scalable, cross-border payment system.
Understanding driver behavior via the use of connected cars can help organizations make data-driven decisions to reduce safety risks, improve commercial driver productivity, and streamline fleet operations. In this webinar by Hazelcast and Intel, we will show a method for the non-intrusive and real-time detection of visual distraction.
