MySQL vs PostgreSQL: What are the differences?
What is MySQL? The world's most popular open source database. The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
What is PostgreSQL? A powerful, open source object-relational database system. PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MySQL and PostgreSQL can be primarily classified as "Databases" tools.
"Sql", "Free" and "Easy" are the key factors why developers consider MySQL; whereas "Relational database", "High availability " and "Enterprise class database" are the primary reasons why PostgreSQL is favored.
MySQL and PostgreSQL are both open source tools. PostgreSQL with 5.38K GitHub stars and 1.79K forks on GitHub appears to be more popular than MySQL with 3.91K GitHub stars and 1.54K GitHub forks.
According to the StackShare community, MySQL has a broader approval, being mentioned in 2965 company stacks & 2944 developers stacks; compared to PostgreSQL, which is listed in 2701 company stacks and 2097 developer stacks.
What is MySQL?
What is PostgreSQL?
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In 2014, Uber began working on Big Data Generation 1. Prior to 2014, all of the company’s data could fit into “a few traditional online transaction processing (OLTP) databases (in [their] case, MySQL and PostgreSQL ).” At that time, engineers were required to write individual code to access and join data across databases, a take made more difficult by the fact that there was no global view of all stored data, which was scattered around several OLTP databases with a “total data size on the order of a few terabytes.”
They chose Vertica as the analytical data warehouse, because of “because of its fast, scalable, and column-oriented design. We also developed multiple ad hoc ETL (Extract, Transform, and Load) jobs that copied data from different sources (i.e. AWS S3, OLTP databases, service logs, etc.) into Vertica.
Uber's early architecture was a monolithic Python backend on top of Postgres. Between 2014 and 2016, Uber moved many applications off of Postgres and onto MySQL, accessed through a sharding layer built in-house called Schemaless.
As the company scaled, Uber encountered issues with scaling writes due to write amplification issues (1 logical write causing 4 physical writes) and inefficient data replication with Postgres. Postgres replication works at the physical level, which means that it's not possible to replicate data between data bases running different versions. This added complexity and risk to upgrades.
MySQL, and the InnoDB storage engine in particular, can do replication at the statement level, which poses less risks and works between versions. Uber also found MySQL's caching and connection pooling capabilities to provide superior performance for their use cases.
The majority of our Clojure microservices are simple web services that wrap a transactional database with CRUD operations and a little bit of business logic. We use both MySQL and PostgreSQL for transactional data persistence, having transitioned from the former to the latter for newer services to take advantage of the new features coming out of the Postgres community.
Most of our Clojure best practices can be summed up by the phrase "keep it simple." We avoid more complex web frameworks in favor of using the Ring library to build web service routes, and we prefer sending SQL directly to the JDBC library rather than using a complicated ORM or SQL DSL.