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.
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.
Setting up servers and configuring software can get in the way of the problems you are trying to solve. With Hazelcast Cloud we take all of those pain points away.
Watch this webinar to learn how you can instantly fire up and then work with Hazelcast Cloud from anywhere in the world. With our auto-generated client stubs for Java, Go, Node.js, Python and .NET, we can have you connected and coding in less than a minute!
With our recent release of Hazelcast IMDG 4.0, we would like to invite you to watch this video, where we will discuss the new features in this release at a high level and talk about how you can take advantage of them.
Hazelcast Cloud delivers enterprise-grade Hazelcast software in the cloud, deployed as a fully managed service. Leveraging over a decade of experience and best practices, Hazelcast Cloud delivers a high-throughput, low-latency service that scales to your needs while remaining simple to deploy. If you’re considering moving to the Cloud, or are looking for an easy ramp on deploying in-memory technology, this white paper on migrating in-memory to the cloud is an informative and helpful resource.
Edge computing complements your cloud deployments by addressing issues related to having data created in remote locations. While businesses today are still in the early stages of edge computing, the expectation is that there will be significant adoption in the next two years. Hazelcast believes now is a good time to explore edge opportunities, and supports such initiatives with in-memory technologies that help drive powerful edge deployments.
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The Infinity Data research, commissioned in collaboration with Intel, examines how companies are addressing the challenge imposed by latency. The research was conducted through a survey of more than 350 IT decision-makers in the US and across industries: financial services, e-commerce, telecommunications, energy, and the public sector.
Hazelcast Jet is a high throughput, low latency, distributed stream processing engine that enables applications with the highest performance. It is a core component of the Hazelcast In-Memory Computing Platform which provides a suite of capabilities for high performance, distributed computing workloads. Fast access data storage, distributed computation, and real-time event stream processing being chief […]
Hazelcast Enterprise features help to simplify the DevOps function for companies that need secure, always-on, low-latency, in-memory processing features. Understanding the feature set of the Enterprise and Enterprise HD editions of the Hazelcast In-Memory Computing Platform will help you run at peak efficiency and performance. Features covered in this paper include: Rolling Upgrades Blue-Green Deployment […]
Hazelcast Jet (part of the Hazelcast In-Memory Computing Platform) is a high performance, scalable, and fault tolerant stream processing engine built for the highest throughput and lowest latency streaming environments. Job submission in Jet is done either using the Hazelcast Client directly from an application, or via the Hazelcast Command Line Interface (CLI). This guide […]
In EMEA, there are many options in payment processing networks tailored to different countries, supporting different transaction scenarios and providing a competitive marketplace to keep processing costs down. Learn how In-memory computing can help banks navigate myriad options without compromising on speed or security, and enabling them to better give their customers the services they want in a more profitable way.
Are you ready to take your algorithms to the next steps and get them working on real-world data in real-time? We will walk through an architecture for taking a machine learning model into deployment for inference within an open source platform designed for extremely high throughput and low latency.
Payment processing systems require extremely high throughput rates as well as millisecond-level latencies. By leveraging the Hazelcast In-Memory Computing Platform, businesses gain a significant performance advantage to successfully process high volumes of transactions. Hazelcast also provides the scalability to easily grow and adapt to changing transaction volumes, which is especially important during heavy purchasing seasons and events with loads that spike well beyond typical levels.
In this white paper, Hazelcast reviews the current state of the US payments markets, including the primary business and technology drivers, and the overarching role that fraud detection plays in ensuring a safe and stable experience for consumers, business, and the network providers.
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