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Category: Ecosystem Integrations

Getting Started with SQL Workbench/J on a Distributed SQL Database

Getting Started with SQL Workbench/J on a Distributed SQL Database

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. In a previous blog we explored the DBeaver database management tool,

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Best Practices for Deploying   Confluent Kafka, Spring Boot & Distributed SQL Based Streaming Apps on Kubernetes

Best Practices for Deploying Confluent Kafka, Spring Boot & Distributed SQL Based Streaming Apps on Kubernetes

In our previous post “Develop IoT Apps with Confluent Kafka, KSQL, Spring Boot & Distributed SQL”, we highlighted how Confluent Kafka, KSQL, Spring Boot and YugabyteDB 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.

Challenges of Streaming Apps

Streaming apps are inherently stateful in nature given the large volume of data managed and that too continuously.

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Spring Data REST Services Powered By Distributed SQL – A Hands-on Lab

Spring Data REST Services Powered By Distributed SQL – A Hands-on Lab

The 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. Annotation configuration and default codes are two examples of such a view.

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Develop IoT Apps with Confluent Kafka, KSQL, Spring Boot & Distributed SQL

Develop IoT Apps with Confluent Kafka, KSQL, Spring Boot & Distributed SQL

In 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 YugabyteDB as their highly scalable, long-term persistent data store. In this post, we show how Confluent Kafka, KSQL, Spring Boot and YugabyteDB can be integrated to develop an application for managing Internet-of-Things (IoT) sensor data.

The Scenario – IoT-Enabled Fleet Management

A trucking company wants to track its fleet of IoT-enabled vehicles that are delivering shipments across the country.

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5 Reasons Why Apache Kafka Needs a Distributed SQL Database

5 Reasons Why Apache Kafka Needs a Distributed SQL Database

Modern 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, applications publish events to a message broker asynchronously. They trust the broker to route the message to the right application,

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YugabyteDB Engineering Update – May 2019

YugabyteDB Engineering Update – May 2019

A lot is happening at YugabyteDB since we announced 1.2, so we thought we’d provide the community with a quick recap of engineering highlights, announcements and shout outs to catch everyone up. Let’s dive in!

Progress on YugabyteDB 2.0

Check out our “Roadmap for YugabyteDB 2.0” to get more details on the exciting features shipping in the next big release this Summer!

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