YugaByte DB

The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

Apache Kafka Distributed SQL How To Kubernetes Spring
June 12, 2019
by Sid Choudhury

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 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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Distributed SQL How It Works
June 6, 2019
by Sid Choudhury

How Data Sharding Works in a Distributed SQL Database

Enterprises of all sizes are embracing rapid modernization of user-facing applications as part of their broader digital transformation strategy. The relational database (RDBMS) infrastructure that such applications rely on suddenly needs to support much larger data sizes and transaction volumes. However, a monolithic RDBMS tends to quickly get overloaded in such scenarios. One of the most common architectures to get more performance and scalability in an RDBMS is to “shard” the data.

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Distributed SQL How To Pivotal Container Service (PKS) Spring
May 30, 2019
by Sid Choudhury

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.

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Distributed SQL How It Works
May 28, 2019
by Rahul Desirazu

How to Handle Runaway Queries in a Distributed SQL Database

Runaway queries are queries that scan through a large set of data. Such queries consume vast amounts of I/O and CPU resources of the database in the background, even if the results appear as harmless timeouts to the end user or the client application. How do runaway queries get executed in the first place, anyway? Everyone who uses databases has at some point or another entered SELECT * from some_large_table,

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Apache Kafka Distributed SQL How To Spring
May 23, 2019
by Sid Choudhury

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 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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Apache Kafka Distributed SQL How It Works
May 21, 2019
by Sid Choudhury

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,

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Distributed SQL Google Spanner How It Works Jepsen Tests
May 15, 2019
by Timur Yusupov

Achieving Fast Failovers After Network Partitions in a Distributed SQL Database

In February of this year, Kyle Kingsbury of Jepsen.io was conducting formal testing of YugaByte DB for correctness under extreme and unorthodox conditions. Obviously, simulating all manner of network partitions is part of his testing methodology. As a result, during his testing he spotted the fact that although nodes would reliably come back after a failure,

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