Thoughts on distributed databases, open source and cloud native
Our previous post dived into the details of the storage layer of YugaByte DB 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.
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Read MoreIn this post, we’ll dive into the architecture of the distributed storage layer of YugaByte DB, 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 YugaByte DB.
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The team at YugaByte is excited to announce that YugaByte DB 1.2 is officially GA! You can download the latest version from our Quick Start page.
YugaByte SQL (YSQL) is our PostgreSQL v11 compatible, distributed SQL API. It is ideal for powering microservices that require low latency,
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Read MoreIn the first post of our series comparing YugaByte DB with PostgreSQL and MongoDB, we mapped the core concepts in YugaByte DB to the two popular databases. This post is a deeper dive into the high availability and transactions architecture of these databases.
Almost all databases including YugaByte DB use replication to ensure that the database remains highly available under failures.
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Read MoreIf you are developing a new distributed application or are extending an existing one with a new set of microservices, chances are you are going to need to store data in a distributed SQL database. The plethora of niche databases that have emerged over the last decade make the task of selecting a database challenging. With many databases, each with its own nomenclature and nuances to choose from,
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Read MoreThis blog post was co-authored by Mikhail Bautin and Kannan Muthukkaruppan
As described in our previous post “How We Built a High Performance Document Store on RocksDB?”, YugabyteDB’s distributed document store (DocDB) uses RocksDB as its per-node storage engine. We made multiple performance and data density related enhancements to RocksDB in the course of embedding it into DocDB’s document storage layer (figure below).
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Read MoreThis blog post was co-authored by Mikhail Bautin and Kannan Muthukkaruppan
RocksDB is a popular embeddable persistent key-value store. First open sourced by Facebook in 2012 as a fork of the Google LevelDB project, it has been adapted over the years to a wide range of workloads including database storage engines and application data caching.
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Read MoreObservability is absolutely vital to operating business-critical data infrastructure at scale. This is why observability is not an afterthought in the YugaByte DB architecture. Every layer of YugaByte DB exposes metrics in the Prometheus format at the /prometheus-metrics endpoint. Given that Prometheus is essentially the de-facto standard for build-your-own infrastructure monitoring and alerting, you can get started with monitoring YugaByte DB in almost no time.
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Read MoreFoundationDB enjoys a unique spot in the transactional NoSQL space given its positioning as a basic key-value database that can be used to build new, more application-friendly databases. Given that many of the guarantees provided by its core engine (such as multi-shard ACID transactions and high fault tolerance) are similar to those provided by YugaByte DB, our users often ask us for a comparison.
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Read MoreIn this short blog post we are going to give you a quick overview of the components that make up a YugaByte DB universe.
YugaByte DB is composed of nodes. We collectively refer to this collection of all nodes as a universe. These nodes can be physical machines, virtual machines or containers (e.g. Kubernetes).
A YugaByte DB universe is made up of one or more clusters.
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