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Scale Out PostgreSQL

Best Practices and Recommendations for Distributed SQL on Kubernetes

Best Practices and Recommendations for Distributed SQL on Kubernetes

YugabyteDB and Kubernetes have very complementary design principles because they both rely on an extensible and flexible API layer, as well as a scale-out architecture for performance and availability. In this blog post we’ll look at best practices and recommendations when choosing Kubernetes as the cluster foundation for a distributed SQL system. This will begin with a review of relevant architectural decisions of the YugabyteDB. Then we’ll walk you through how to handle the provisioning,

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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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2019 Distributed SQL Summit Confirmed Speakers & Schedule is Live!

2019 Distributed SQL Summit Confirmed Speakers & Schedule is Live!

YugaByte is excited to announce that speaker schedule for this year’s Distributed SQL Summit is live!

Distributed SQL Summit is a full day of talks from experts on what it takes to build, deploy and scale distributed SQL databases in the cloud and on Kubernetes.

Presented in partnership with PostgresConf, the inaugural Distributed SQL Summit is taking place on September 20, 2019 in San Jose,

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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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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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PostgreSQL How-to: SportsDB Running on a Distributed SQL Database

PostgreSQL How-to: SportsDB Running on a Distributed SQL Database

SportsDB is a sample dataset compiled from multiple sources, encompassing a variety of sports including football, baseball, ice hockey and more. It also cross-references many different types of content media. It is capable of supporting queries for the most intense of sports data applications, yet is simple enough for use by those with minimal database experience. The database itself is comprised of over 100 tables and just as many sequences, unique constraints, foreign keys and indexes.

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YugabyteDB Engineering & Community Update – July 19, 2019

YugabyteDB Engineering & Community Update – July 19, 2019

We are pleased to announce that YugabyteDB 1.3.0 is live! You can read the release notes of this and previous versions here. This release is shipping with 24 new features, enhancements and bug fixes. Beyond enhancements and fixes, the other big news is that we have open sourced the entire core database code! This means that previously closed features like distributed backups, data encryption and replicas are now open sourced. This also means that upcoming features like change data capture and 2 datacenter deployments will open source as well.

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YugabyteDB Engineering & Community Update – July 10, 2019

YugabyteDB Engineering & Community Update – July 10, 2019

We are pleased to announce that YugabyteDB 1.2.12 is live! You can read the release notes of this and previous versions here. This release is shipping with 11 new enhancements and bug fixes. This also means we are getting closer to our 2.0 release at the end of the Summer in which the YSQL API will become generally available.

What’s YSQL? It’s YugabyteDB’s PostgreSQL-compatible, distributed SQL API.

To learn more about what’s shipping in the 2.0 release check out “YugabyteDB 2.0: A Distributed SQL Roadmap.”

[#1446] Visually Inspect YSQL Commands

This new feature is especially useful to SQL developers.

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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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