The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

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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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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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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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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YugaByte DB 1.2 Passes Jepsen Testing

You can join the discussion about the results on HackerNews here.

Last year we published our DIY Jepsen testing results – including the tests and failure modes implemented as well as the bugs found. We recently engaged Kyle Kingsbury, the creator of the Jepsen test suite, for an official analysis and are happy to report that YugaByte DB 1.2 formally passes Jepsen tests using the YCQL API.

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