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.
Large-scale computations need integration of transactional, operational, and historical data into a single platform. Connecting all the relevant data sources is hard enough, but procuring the compute power and storage space adds another level of complexity. You need these compute-intensive jobs to always complete within stringent SLAs, so you need high speed and efficient use of hardware resources. And you only want the resources you need, only when you need them.
Hazelcast provides the foundation to develop and deploy fast, highly scalable applications for you to run large-scale calculations, simulations, and other data- and compute-intensive workloads.
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Real-time decision-making entails immediately analyzing a comprehensive set of information to take the best action, often without any human intervention. But overwhelming complexity arises from disparate data silos plus the many moving parts that need to be bolted together in a real-time system. You end up struggling with low agility, putting your operations at a disadvantage. And you know it does not help to simply add more of the same components to your infrastructure.
Hazelcast enables optimal real-time decisions thanks to a low-latency, distributed memory architecture for data and computations.
Online transactions are often constrained by bottlenecks while accessing databases and other repositories spread across your organization. Building optimized, transaction-based applications on these silos is difficult because of performance, auditing, security, risk, and data safety reasons. You are forced to make trade-offs that lead to an unacceptable user experience that negatively impacts your business.
Hazelcast accelerates your transactions by significantly reducing data access latency via in-memory storage of data sourced from your many disparate data stores.
Are you a developer, software engineer or architect looking to apply in-memory technologies to your current architecture? Are you looking to deliver ultra-fast response times, better performance, scalability and availability? Are you seeking new tools and techniques to manage and scale data and processing through an in-memory-first and caching-first architecture?
Companies need a data-processing solution that increases the speed of business agility, not one that is complicated by too many technology requirements. This requires a system that delivers continuous/real-time data-processing capabilities for the new business reality.
This white paper, written by Java Champion Ben Evans, provides an introduction for architects and developers to Hazelcast®’s distributed computing technology.
Contact us now to learn more about how our in-memory computing platform can help you leverage data in ways that immediately produce insight and actions.