The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

Announcing YugabyteDB on Crossplane, the Open Source Multicloud Control Plane

We are excited to announce that YugabyteDB is now available as a self-managed database service on Crossplane, the open-source multicloud control plane. Built on top of our recent Rook Kubernetes Operator for YugabyteDB, this offering makes YugabyteDB one of the first distributed SQL databases available on Crossplane.

Benefits of the Joint Solution

With Crossplane as the single control plane,

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9 Techniques to Build Cloud-Native, Geo-Distributed SQL Apps with Low Latency

This post is an in-depth look at the various techniques that applications needing low latency and high availability can leverage while using a geo-distributed SQL database like YugabyteDB so that the negative impacts of an high-latency, unreliable Wide Area Network (WAN) are minimized.

Geo-Distributed SQL is the Future of RDBMS

Enterprises are increasingly moving to cloud-native applications powered by microservices architecture.

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GO-JEK’s Performance Benchmarking of CockroachDB, TiDB & YugaByte DB on Kubernetes

Iqbal Farabi and Tara Baskara, Systems Engineers from GO-JEK Indonesia, recently presented the results of their benchmarking of cloud native databases on Kubernetes at KubeCon Europe in Barcelona. The three databases they benchmarked were CockroachDB, TiDB and YugaByte DB. This post brings their presentation (video recording) and slides (PDF) to the attention of our readers.

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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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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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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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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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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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