Every SQL execution in PostgreSQL and therefore in YugabyteDB YSQL takes time to process. A common way to identify how much is time spent on processing is to use the pg_stat_statements view in the database. However, the time visible in pg_stat_statements might differ from the time a database client registers for the execution. Where does this difference come from? Let’s take a look.
Learn how to best use Query Planner hints in the YugabyteDB database to optimize business queries based on how applications expose them. Walk through a use case that utilizes data sets from two popular TV shows to find total viewership per season, episode, etc.
After officially launching Yugabyte University in early 2022, we are happy to share a major milestone! Ten thousand amazing students are enrolled in various self-paced and instructor-led courses, certification programs, and builder workshops to better build their skillsets around distributed SQL and YugabyteDB. Read this blog for an overview of what’s currently available, including links to specific learning experiences.
YugabyteDB is a 100% open source, distributed SQL database system. This single phrase expresses two distinct notions: a SQL database system, and a distributed database system. Historically, these notions were mutually exclusive. But current technology allows a single system to implement both notions. YugabyteDB does this with its two-layer architecture: an extensible query processing layer and a distributed document store.
In this blog post, we explain how YugabyteDB’s two-layer architecture works and compare it against other popular databases.
Welcome back to our bi-weekly tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation, and blogs that have been published recently. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub, or Stack Overflow. Let’s dive in:
When looking to pool your connections with YugabyteDB many users take a look at PgBouncer,
Our previous post dived into the details of the storage layer of YugabyteDB called DocDB, a distributed document store inspired by Google Spanner. This post focuses on Yugabyte SQL (YSQL), a distributed, highly resilient, PostgreSQL-compatible SQL API layer powered by DocDB. A follow-up post will highlight the challenges faced and lessons learned when engineering such a database.
Yugabyte SQL (YSQL) is a distributed and highly resilient SQL layer,
In this post, we’ll dive into the architecture of the distributed storage layer of YugabyteDB, which is inspired by Google Spanner’s design. Our subsequent post covers the Query Layer, where the storage layer meets PostgreSQL as the SQL API. Finally, here is a follow-up post that highlights the key technical challenges we faced while engineering a distributed SQL database like YugabyteDB.
YugabyteDB is comprised of two logical layers,
YugaByte SQL (YSQL) is our PostgreSQL v11 compatible, distributed SQL API. It is ideal for powering microservices that require low latency, internet scale, geographic data distribution and extreme resilience to failures but want the data modeling flexibility of SQL (joins,
YugaByte is excited to be at KubeCon today to announce Kubernetes StatefulSets support for our distributed SQL API which complements the transactional NoSQL APIs already generally available. YSQL is YugabyteDB’s PostgreSQL-compatible Distributed SQL API (currently in Beta). This new feature, available in YugabyteDB 1.1.7, cloud-native applications and microservices can rely on SQL and NoSQL to take full advantage of Kubernetes StatefulSets to power horizontally scalable, highly fault-tolerant data services,