The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

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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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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YugaByte DB Engineering Update – May 2019

A lot is happening at YugaByte DB 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 YugaByte DB 2.0

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

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Why Distributed SQL Beats Polyglot Persistence for Building Microservices?

Today’s microservices rely on data with different models and read/write access patterns. Polyglot persistence, first introduced in 2008, states that each such data model should be powered by an independent database that is purpose-built for that model. This post highlights the loss of agility that microservices development and operations suffer when adopting polyglot persistence. We review how distributed SQL serves as an alternative approach that doesn’t compromise this agility.

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6 Technical Challenges Developing a Distributed SQL Database

You can join the discussion on HackerNews here.

We crossed the three year mark of developing YugaByte DB in February of this year. It has been a thrilling journey thus far, but not without its fair share of technical challenges. There were times when we had to go back to the drawing board and even sift through academic research to find a better solution than what we had at hand.

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Distributed SQL on Google Kubernetes Engine (GKE) with YugaByte DB’s Helm Chart

The glory days of the heavy-weight hypervisor are slowly fading away, and in the last few years, containerization of applications and services is the new reality. With containerization, enterprises can prototype, deploy, and meet scale demands more quickly. To systematically and efficiently manage these large-scale deployments, enterprises have bet on technologies like Kubernetes (aka k8s), a powerful container orchestrator, to get the job done.

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How to Achieve High Availability, Low Latency & GDPR Compliance in a Distributed SQL Database

Today’s developers understand that the key requirement to converting and retaining customers is all about delivering fast and responsive experiences, while remaining resilient to failures and compliant with data governance regulations. YugaByte DB is purpose built for geo-distributed applications that require high availability, high performance and regulatory compliance. In this blog, we are going to “look under the hood,” to explore exactly how YugaByte DB distributes data across multiple clouds,

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