MongoDB’s dynamic schema is powerful and challenging at the same time. In Java, a common approach is to use an object-document mapper to make the schema explicit in the application layer. Kotlin takes this approach even further by providing additional safety and conciseness. This post shows how the development with MongoDB can benefit from Kotlin and which patterns turned out to be useful in practice. We’ll also cover best practices for coding and schema design.
The term Microservices is quite vague as it leaves many questions unanswered. Contrarily, a Self-Contained Systems subsumes concrete recommendations and best practices that can guide you to create an application which is resilient and independent. But how can we implement such a system? At Spreadshirt, we build an application following the recommendations of a Self-Contained System. In this post, I’ll show you which technologies we used and which challenges we faced.
In the last blog post I shared my personal experiences with the course ”MongoDB for Java Developer” (M101J). The second part revolves around the content. I summarize my personal takeaways and add some personal assessment in terms of the content.
I attended the course “MongoDB for Java Developer” (M101J). It was fun and I learned a lot about MongoDB. I like to share my gained knowledge and experience in a two-part series. In this first part I assess the course and state, whether or not the course is worth the time.
Relational Databases seem to be the universal hammer in the toolbox of every developer. There is the notion that you can solve every problem with it – you just have to smash hard enough. However, if you use relational databases out of habit, you can easily run into troubles when it comes to schema evolution, scalability, performance or certain domains. This post discusses the strength and weaknesses of relational databases and points out alternatives.