Find out more

How It Works

Getting Started with PostgreSQL Triggers in a Distributed SQL Database

Getting Started with PostgreSQL Triggers in a Distributed SQL Database

Triggers are a basic feature that all monolithic SQL systems like Oracle, SQL Server and PostgreSQL have supported for many years. They are very useful in a variety of scenarios ranging from simple audit logging, to advanced tasks like updating remote databases in a federated cluster. In this blog, we’ll look at examples of INSERT, UPDATE and INSTEAD OF triggers in Yugabyte DB.

What’s Yugabyte DB? It is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner.

Read more

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,

Read more

Low Latency Reads in Geo-Distributed SQL with Raft Leader Leases

Low Latency Reads in Geo-Distributed SQL with Raft Leader Leases

Note: This post contains interactive animations that explain how some of these complex algorithms work. Please view this post in a suitable media (at least 1000px by 600px screen resolution) for best results.

In this blog post, we are going to dive deep into the read performance of Raft – why read performance can take a hit and how it can be improved using leader leases. Additionally, we will also look at how to make the correctness guarantees around leader leases stronger.

Read more

How Data Sharding Works in a Distributed SQL Database

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 architectural patterns used to scale an RDBMS is to “shard” the data. In this blog, we will learn what data sharding is and how it can be used to scale a SQL database.

Read more

How to Handle Runaway Queries in a Distributed SQL Database

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, only to realize they forgot to add a LIMIT n clause.

Read more

5 Reasons Why Apache Kafka Needs a Distributed SQL Database

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, applications publish events to a message broker asynchronously. They trust the broker to route the message to the right application,

Read more

Achieving Fast Failovers After Network Partitions in a Distributed SQL Database

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 YugabyteDB 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, the recovery itself was taking roughly 25 seconds to occur. We certainly didn’t like the sound of that!

Read more

6 Technical Challenges Developing a Distributed SQL Database

6 Technical Challenges Developing a Distributed SQL Database

You can join the discussion on HackerNews here.

We crossed the three year mark of developing the YugabyteDB database in February of 2019. 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.

Read more

Explore Distributed SQL and YugabyteDB in Depth

Discover the future of data management.
Learn at Yugabyte University
Get Started
Browse Yugabyte Docs
Explore docs
PostgreSQL For Cloud Native World
Read for Free