[MapR Newsletter] What's Dataware?

John Schroeder, CEO, Chairman of the Board Edge-to-Cloud Architecture Is Getting Big Wins and Going More Mainstream Fast   Recently we have had more big wins in what I am seeing becoming more mainstream everyday – the edge-to-cloud architecture. A few thoughts on what's happening and how it may give you some things to think about as you pursue AI/ML in an increasingly edge-first or distributed environment. I am really excited about our win in the robodrive world. One of the world's leading automotive manufacturers has selected the MapR Data Platform as the foundation for their next-gen autonomous vehicle program. The architecture requires consistency from edge to multi-cloud and also needs to support a variety of processing and analytic/AI tools easily. The ability to have robust, persistent, and replayable streaming data is critical, as is mission-critical capability and reliability, of course. MapR's success here is because of our platform's shrink-to-fit edge footprint and its ability to transparently create a global data fabric that spans the edge to multiple clouds. In fact, our current wins are being driven by this unique capability. The concepts here are very widely applicable, and we have already seen similar concepts applied in energy production and in smart healthcare medical equipment. I am also pleased our concept of dataware – a new layer in the modern data stack – is resonating well with customers and prospects. Dataware is an abstraction layer that allows you to manage your entire data ecosystem from one platform, decoupled from any dependencies. It gives you a consistent approach to manage, secure, govern, and protect all data across your enterprise. By optimizing the entire data lifecycle, dataware powers applications that simultaneously require real-time analytics and AI/ML. Dataware is the next critical layer in the enterprise stack, much like middleware, applications, and hardware are today. We are also proud to be an early and aggressive adopter of Kubernetes technology, including Kubeflow. Our first major new product announcement was on April 2nd showcasing our tech preview of separating compute and storage. You can spin up apps in Kubernetes in the cloud or on-premises, while having easy and secure access to stateful data in the MapR data platform. This has the advantages of greater elasticity for many types of workloads. Check out our announcement below. I invite you to find out more about the powerful notion of dataware and also to talk to us about how our edge-to-cloud architecture could add value to your initiatives.   WHAT'S DATAWARE?         Accelerate the Separation of Compute and Storage   MapR recently announced groundbreaking innovations for independently scaling compute and storage by continuing to take a leadership role in embracing Kubernetes and containers. With this announcement, MapR simplifies the entire process of spinning up compute when and where you need it. With deeper integrations with Kubernetes, MapR now powers your organization's ability to:     • Better handle compute needs that are bursty and unpredictable • Run compute jobs (Spark and Drill queries) in a truly multi-tenant environment, ensuring tenants do not starve each other of precious resources such as CPU and memory • Easily deploy and scale compute across different types of environments, including on-premises, public, and hybrid cloud • More effectively manage use cases (e.g., next-gen applications and data lakes) in an increasingly hybrid cloud environment   LEARN MORE         Build Machine Learning Projects - Free Training   Artificial intelligence and machine learning help businesses translate data into direct business value, but it's estimated that only 20% of ML projects ever make it into production. It's crucial for businesses to understand how to prepare, plan, and execute on a well-defined, action-oriented strategy. Our new Build a Machine Learning Project course introduces the most important aspects of putting together a machine learning project plan. In a repeatable process of six steps that can be followed for any machine learning workflow, you will learn how companies are implementing ML with MapR to maximize their business results.   GET STARTED         Test Drive MapR on the Web or in a Free VM Sandbox   What do you call the difference between knowledge and information? Experience! Experiential learning is a core part of how we humans learn new things. At MapR, we know this all too well, and it's why we offer multiple ways for you to try our product. Whether on the web or in a free VM sandbox, you can experience firsthand how MapR can be your data platform for AI and analytics.   TRY MAPR         Additional Resources     Download the eBook Today!   Find an Event Near You!   Download the eBook Today!

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