The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a blog series. This is part 5: Best Practices for Building a Cloud-Native Data Warehouse or Data Lake.
JavaOne 2016 Trends: Besides focus on Java platform updates (Java 9, Java EE 8, etc.), I saw three hot topics, which are highly related to each other: Microservices, Docker and Cloud. I also talked about this topic from a middleware perspective. See my slides and lessons learned.
I used SmartGWT in our last project (duration: 6 months) – that is a component library for the Google Web Toolkit (GWT). I wanna share my experiences with that component library in the following. I show pros and cons of SmartGWT. Then I explain why I would use only a the client side of SmartGWT in future projects. I used SmartGWT Power 2.3 and GWT 2.0. All information is my personal opinion!
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