How To

Getting Started with PGAdmin on a Distributed SQL Database

Getting Started with PGAdmin on a Distributed SQL Database

If you’re a database developer, you already understand the importance of a tool to manage your databases. Whether it is for creating schemas, ad-hoc querying, backups, or diving deeper to troubleshoot a database issue, a database tool can make your life much easier and increase your productivity. In a previous post we covered how to get started with DBeaver, and in this post we’ll show you how to get up and running with YugabyteDB and PGAdmin.

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PostgreSQL How To: Installing the Chinook Sample DB on a Distributed SQL Database

PostgreSQL How To: Installing the Chinook Sample DB on a Distributed SQL Database

In this post we are going to walk you through how to download and install the PostgreSQL version of the Chinook sample DB on the YugabyteDB distributed SQL database with a replication factor of 3.

What’s YugabyteDB? It’s a high performance distributed SQL database for global, internet-scale apps. YugabyteDB is a PostgreSQL-compatible database. Similar to Google Spanner, YugabyteDB gives you all the scalability characteristics of NoSQL, without sacrificing the ACID transactions or strong consistency you are accustomed to with PostgreSQL.

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Getting Started with DBeaver on a Distributed SQL Database

Getting Started with DBeaver on a Distributed SQL Database

Editor’s note: Updated July 7, 2020 with the new DBeaver wizard

If you’re a database developer, you know that you need different SQL statements for creating schemas, ad-hoc querying, initiating backups, or troubleshooting. For these scenarios, finding the right graphical tool can speed up these tasks and make you more productive. Over the years, the PostgreSQL community has developed several open source graphical tools for managing PostgreSQL databases, visualizing the datasets it contains,

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Relational Data Modeling with Foreign Keys in a Distributed SQL Database

Relational Data Modeling with Foreign Keys in a Distributed SQL Database

Note added on October 31, 2019

A lot has happened since this post was published in July 2019. Back then, the current YugabyteDB version was 1.2.10. And now, it’s 2.0.3. My original text included some caveats and comments like “Until this support is added in a future release…”. Now, no caveats are needed. I therefore revised my text and the companion downloadable code to remove all reference to those earlier, interim,

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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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