Thoughts on distributed databases, open source and cloud native
Although most databases ship with a command line utility to administer the instance, these utilities often come with a steep learning curve. If using the command line and learning sometimes arcane syntax makes you uncomfortable, there are graphical tools that can help you speed up many daily DBA tasks. In fact, you can find a comprehensive list of tools on the PostgreSQL wiki here.
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Read MoreIn our previous post “Develop IoT Apps with Confluent Kafka, KSQL, Spring Boot & Distributed SQL”, we highlighted how Confluent Kafka, KSQL, Spring Boot and YugaByte DB can be integrated to develop an application responsible for managing Internet-of-Things (IoT) sensor data. In this post, we will review the challenges and best practices associated with deploying such a stateful streaming application on Kubernetes.
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Read MoreThe Spring application development framework is arguably the most popular framework among Java developers. However, given its extensive breadth and depth, it can be difficult to learn for new users. As the name suggests, Spring Boot makes it easy to boot up with the Spring framework. It shortens development time by taking an opinionated view of the framework and the associated third-party libraries.
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Read MoreIn our previous post “5 Reasons Why Apache Kafka Needs a Distributed SQL Database”, we highlighted why Kafka-based data services need a distributed SQL database like YugaByte DB as their highly scalable, long-term persistent data store. In this post, we show how Confluent Kafka, KSQL, Spring Boot and YugaByte DB can be integrated to develop an application for managing Internet-of-Things (IoT) sensor data.
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Read MoreModern enterprise applications must be super-elastic, adaptable, and running 24/7. However, traditional request-driven architectures entail a tight coupling of applications. For example, App 1 asks for some information from App 2 and waits. App 2 then sends the requested information to App 1. This sort of app-to-app coupling hinders development agility and blocks rapid scaling.
In event-driven architectures,
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