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.
Operating in today’s always-on, high-volume, high-speed, high-expectation world requires a different level of processing enablement. When microseconds can mean the difference between success and failure, Hazelcast in-memory caching solutions can deliver blinding speed with scalable and flexible data caching.
Fraud has grown to epidemic proportions as our digital lives become increasingly interconnected, dependent, and exploitable. In-memory solutions such as Hazelcast IMDG and Jet enable real-time fraud detection or fraud detection machine learning at speeds and scale that drive security enablement to a new level.
Embed stream processing into your enterprise applications with Hazelcast to immediately process and respond to data.
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In a world where billions of devices are constantly streaming data into your IT systems, Hazelcast In-Memory Computing Platform is the ideal solution for managing your IoT ecosystem.
Hazelcast enables organizations to seamlessly integrate with JCache. These operations can help to scale out applications and manage their high-speed access to their frequently used data. Hazelcast smoothly achieves its caching potential with a 100 percent compliant implementation that transparently registers with the JCache subsystem.
Use Hazelcast as a drop-in replacement for Memcached, with the added benefits of elastic scaling (much larger cache sizes), ultra-fast performance, high availability, and easy maintenance. No changes are required in your apps/clients to upgrade to Hazelcast other than pointing to the Hazelcast cluster. Hazelcast has been used in production as an alternative to Memcached as well as a plug-in enhancement.
Hazelcast can be used as a fast and lightweight messaging system that lets applications communicate in real time at high speed. You can write to Hazelcast in a publish-subscribe paradigm, which means your applications can write (“publish”) to specific channels called “topics,” and then one or more subscribers can read the messages from that topic.
Microservices help simplify development, testing, deployment, fault tolerance, and scaling. Now gain higher throughput and lower latency with an ultra-fast, lightweight infrastructure built for running modern enterprise architectures.
Learn how in-memory technologies can satisfy the EU Revised Payment Service Directive (PSD2) in support of Open Banking.
Enterprises demand proven high-performance transactional systems that can scale out elastically, and provide concurrency across distributed application nodes. This often drives the purchase of expensive and proprietary solutions such as Oracle Coherence across a host of projects. Although Coherence is a mature product in the financial services sector, several critical issues are driving projects to migrate to Hazelcast in many customers worldwide.
Hazelcast in-memory solutions modernize payment processing, accelerate bank and merchant performance, and improve customer experience.
Hazelcast Jet provides all the necessary tools to build a real-time stream processing application. It is a powerful processing framework for querying data streams on top of an elastic in-memory storage system, where the process may ultimately store its results.
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