Now that we've learned how to set up and run a Spring Boot app using Eclipse IDE and CLI, we'll see how to build a microservices application using Spring Boot.
Like all big data, master data offers important opportunities for machine learning analytics. Embedded analytics of anonymized master data can yield powerful insights.
This tutorial continues this microservices series by showing the downsides of monoliths and an example of microservices architecture to better your understanding.
There are many concepts, theories, and facts related to big data and its popularity — which is what this article is all about. I’ll start with an introduction to big data and then take at look at its future.
Learn how to increase the speed of your high-traffic .NET applications by optimizing Entity Framework Core, providing faster access to relational databases.
Are projects like Apache Spark about to get a serious boost? In this post, we learn about vectorized algorithms in Java, and what it means for the world of big data.
Learn how the Microservices Dashboard app helps you visualize your microservices architecture, how to set it up, and what functionalities its aggregators provide.
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