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.
The most common theme we hear about stream processing is how to make it easier. Many IT professionals understand the value that streaming data provides, but they still see a barrier to adoption due to the complexity of existing stream processing technologies.
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Looking for info on our live events? We're busy coordinating developer events at the moment, so please check back in a few days for the latest info. In the meantime, check out our free, on-demand training.
This case study on how Airbus Defence and Space uses Hazelcast is a great example of how ease-of-use goes a long way in helping engineers build critical systems for large-scale initiatives.
Blue/green deployment refers to a software technique that can be used to reduce or even eliminate systems downtime and its associated business risk by deploying two mirrored production environments referred to as Blue and Green. This white paper will walk you through these deployments, the features, and several use cases.
This talk gives you a gentle introduction into consistency models and will help you with reasoning about trade-offs.
There are common themes when people describe their reasons for rearchitecting legacy business applications, at a technical level: Speed & Scalability. At a business level: The need to gain new insights flowing from an increasing stream of data. These legacy applications commonly centre around some central datastore such as a relational database. Moving away from this architecture requires massive migration effort. The costs and risks associated with such an effort can sometimes be prohibitive for business owners, you can’t just rip out your relational database.
Hazelcast Jet® is an application embeddable, distributed computing platform for fast processing of big data sets. The Hazelcast Jet architecture is high performance and low latency driven, based on a parallel, streaming core engine which enables data-intensive applications to operate at near real-time speeds.
Hazelcast Jet is built on top of Hazelcast IMDG®, the leading open source in-memory data grid with tens of thousands of installed clusters. Hazelcast Jet processing jobs take full advantage of the distributed in-memory data structures provided by Hazelcast IMDG
Read this e-book from RTInsights to get an overview of stream processing, including the popular use cases and what to plan for.
David Brimley, Financial Services Industry Consultant, Hazelcast, speaks to FinextraTV about what financial services firms are doing with machine learning and what firms should consider as they progress through their machine learning journey. He explains how streaming data fits in financial services, how firms can ease into streaming without going through a complete re-architecture of their systems and how financial services technologists need to keep an eye on developments in In-memory computing, Cloud and Containerization."
Listen to this on-demand webinar hosted by Finextra, as industry experts discuss the imminent collision of open banking and instant payments. As the payments industry evolves, problems and pressures created by the need for end-to-end security and fraud risks has an impact on the speed of processing. At the same time, increased commerce, a culture of instant gratification, and the digitalization of services, as well as the increasing convergence on the mobile, means speed is of the essence.
Read this white paper from RTInsights on how IoT/edge computing can open new up opportunities in your enterprise.
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