YugabyteDB 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 YugabyteDB distributes data across multiple clouds, regions and availability zones.
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,
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In this post, we dive into the architecture of the distributed storage layer of YugabyteDB, which is inspired by Google Spanner’s design
The team at YugaByte is excited to announce that YugabyteDB 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, internet scale, geographic data distribution and extreme resilience to failures but want the data modeling flexibility of SQL (joins,
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In this post, we comparethe high availability and transactions architecture of PostgreSQL and MongoDB to that of YugabyteDB.
In this post, we reviewed the building blocks of the YugabyteDB and mapped them to the corresponding concepts (if any) in PostgreSQL and MongoDB.
This 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.
In this post, we explain our rationale for selecting RocksDB as a foundational building block for YugabyteDB.
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FoundationDB 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 the YugabyteDB database, our users often ask us for a comparison. These users are essentially trying to understand whether they should build their app directly using one of the three YugabyteDB APIs or should they explore/build a new database layer on FoundationDB first.
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This benchmarking blog comparing YugabyteDB vs CockroachDB highlights key differences in handling distributed SQL workloads, emphasizing performance and feature advantages.
If you work with databases, at some point you are going to need to get data in and out them using a format that can be consumed by a completely different system. YugabyteDB makes use of CSV files to make this as easy as possible. The CSV format is arguably the most universally portable way to get data migrations accomplished.
TL;DR – YugabyteDB makes use of Cassandra’s COPY FROM command and a forked version of Cassandra’s Bulk Loader to get data into the system.
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