What is MySQL?

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.
MySQL is a tool in the Databases category of a tech stack.
MySQL is an open source tool with 5K GitHub stars and 1.9K GitHub forks. Here鈥檚 a link to MySQL's open source repository on GitHub

Who uses MySQL?

Companies
4347 companies reportedly use MySQL in their tech stacks, including Airbnb, Uber, and Netflix.

Developers
29660 developers on StackShare have stated that they use MySQL.

MySQL Integrations

Travis CI, Slick, Datadog, Amazon DynamoDB, and Matomo are some of the popular tools that integrate with MySQL. Here's a list of all 215 tools that integrate with MySQL.

Why developers like MySQL?

Here鈥檚 a list of reasons why companies and developers use MySQL
Private Decisions at about MySQL
Private to your company

Here are some stack decisions, common use cases and reviews by members of with MySQL in their tech stack.

mahmoud eskandari
mahmoud eskandari
Vue.js
Vue.js
GitLab CI
GitLab CI
GitHub
GitHub
Go
Go
PHP
PHP
MySQL
MySQL

if we know any tool It will be the best tool for us.

Tools don't matter

Understanding what we do is important. My stack: Vue.js GitLab CI GitHub Go PHP MySQL Percona MySQL

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MySQL
MySQL

Hosted Cloud SQL instance in Google Cloud MySQL

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James Wallace
James Wallace
at James Wallace | 1 upvotes 0 views
MySQL
MySQL

relational database MySQL

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MySQL
MySQL

Database MySQL

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Node.js
Node.js
Ubuntu
Ubuntu
MySQL
MySQL
npm
npm
Framework7
Framework7
Vue.js
Vue.js
Webpack
Webpack
nginx
nginx
#Lenovo
#HapiJS
#Framework7
#Plaid

I just designed, developed, and deployed my own budgeting app, dailybudget.cc, which allows me to automate my budgeting the way I have always done it, in a way that I could never fully capture with other budgeting apps, such as Mint, EveryDollar, or YNAB. I spent 4 years from the time I first had the idea to the time I actually sat down to design it and start development. During this time I evaluated many other budgeting app solutions, and had even architected a prototype that I never ended up using. But boy, have technologies come much further in 4 years.

Though my first prototype used Java and Tomcat, I completely abandoned those 4 years later in favor of Node.js technologies, which I have found are equally as stable, more flexible (for better or for worse), and capable of significantly more rapid development. Since what I have deployed now is in beta and is primarily for limited user use, I favored rapid development over slower development where I would write more automated unit tests. I chose to build the app as a HTML5 web application (rather than native iOS or Android, for now), and I used a separated API backend/Web frontend model. My target platform for use with the app is mobile handheld touch devices, though it can work on any laptop or desktop with a touchscreen. Given these design targets, many of the technologies I chose were because of familiarity with them as well as a strong online community, and some technologies I chose that I had to learn anew, because they appeared to fit my needs.

My entire app runs on a #lenovo IdeaCentre desktop on my home network, on which I have installed Ubuntu 18.04. Ubuntu is something I have switched to after a long time of use and familiarity with RedHat Enterprise Linux and CentOS, because the online support for Ubuntu is now tremendous, and there is so much documentation and examples online of how to configure and use Ubuntu; not to mention I have not been thrilled with the direction new releases of CentOS. Ubuntu is also a good environment for development - it is so easy to follow the many online examples. Lastly, I may migrate my app and configuration to Amazon AWS, which also uses Ubuntu for its EC2 Linux VMs, so having Ubuntu now is helpful for that prospect.

The API backend uses Node.js, with #HapiJS as the API server framework and MySQL as my persistence database. HapiJS is something I have had familiarity with and is just a phenomenal framework to plug into and configure, especially if you use it for a route-based API. #Mysql has a great online community. I could've used PostgreSQL too, but I am more familiar with MySQL. Also, if I migrate to Amazon AWS, Amazon's RDS uses MySQL. I use npm as a one-stop-shop package manager and environment manager.

The Web frontend uses a combination of Framework7 and Vue.js. I cannot evangelize Framework7 enough! It is a fantasic tool by @nolimits4web (GitHub) that is really easy to use, really well thought out, and really performant. Framework7 simulates the native iOS or Android (Google Material) experiences, all using HTML5 constructs (HTML+CSS+JS). Vue.js is another very fantastic binding and frontend framework which has a good online community and is well documented and easy to use. I had to choose between VueJS and ReactJS, and ultimately chose VueJS over ReactJS because it seemed to favor more rapid development with less ramp-up time, whereas I understood ReactJS to be more of an enterprise level framework (though still good for smaller projects like mine). When using Framework7 with VueJS, NodeJS is used along with Webpack to transpile my code into browser-friendly JavaScript, HTML, etc. Webpack was nice to use because it has a hot-deploy development mode to enable rapid development without me having stop, recompile, and start my server (this was one of several reasons against using Java with Tomcat). I had no familiarity with Framework7, VueJS, or Webpack prior to this project.

I use nginx as my web server and have the API running behind a reverse proxy, and all of the web frontent content hosted as static content.

I use the plaid API to sync my bank transactions to my database. This is another fantastic framework (though not free beyond development use) that it turns out is extremely easy to use for the complex job that it solves.

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MySQL
MySQL

Database MySQL

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Public Decisions about MySQL

Here are some stack decisions, common use cases and reviews by companies and developers who chose MySQL in their tech stack.

Nick Rockwell
Nick Rockwell
CTO at NY Times | 30 upvotes 895.6K views
atThe New York TimesThe New York Times
MySQL
MySQL
PHP
PHP
React
React
Apollo
Apollo
GraphQL
GraphQL
Node.js
Node.js
Kafka
Kafka
Apache HTTP Server
Apache HTTP Server

When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

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Tim Abbott
Tim Abbott
Founder at Zulip | 23 upvotes 343.5K views
atZulipZulip
PostgreSQL
PostgreSQL
MySQL
MySQL
Elasticsearch
Elasticsearch

We've been using PostgreSQL since the very early days of Zulip, but we actually didn't use it from the beginning. Zulip started out as a MySQL project back in 2012, because we'd heard it was a good choice for a startup with a wide community. However, we found that even though we were using the Django ORM for most of our database access, we spent a lot of time fighting with MySQL. Issues ranged from bad collation defaults, to bad query plans which required a lot of manual query tweaks.

We ended up getting so frustrated that we tried out PostgresQL, and the results were fantastic. We didn't have to do any real customization (just some tuning settings for how big a server we had), and all of our most important queries were faster out of the box. As a result, we were able to delete a bunch of custom queries escaping the ORM that we'd written to make the MySQL query planner happy (because postgres just did the right thing automatically).

And then after that, we've just gotten a ton of value out of postgres. We use its excellent built-in full-text search, which has helped us avoid needing to bring in a tool like Elasticsearch, and we've really enjoyed features like its partial indexes, which saved us a lot of work adding unnecessary extra tables to get good performance for things like our "unread messages" and "starred messages" indexes.

I can't recommend it highly enough.

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Julien DeFrance
Julien DeFrance
Principal Software Engineer at Tophatter | 16 upvotes 1.3M views
atSmartZipSmartZip
Rails
Rails
Rails API
Rails API
AWS Elastic Beanstalk
AWS Elastic Beanstalk
Capistrano
Capistrano
Docker
Docker
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
MySQL
MySQL
Amazon RDS for Aurora
Amazon RDS for Aurora
Amazon ElastiCache
Amazon ElastiCache
Memcached
Memcached
Amazon CloudFront
Amazon CloudFront
Segment
Segment
Zapier
Zapier
Amazon Redshift
Amazon Redshift
Amazon Quicksight
Amazon Quicksight
Superset
Superset
Elasticsearch
Elasticsearch
Amazon Elasticsearch Service
Amazon Elasticsearch Service
New Relic
New Relic
AWS Lambda
AWS Lambda
Node.js
Node.js
Ruby
Ruby
Amazon DynamoDB
Amazon DynamoDB
Algolia
Algolia

Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

Future improvements / technology decisions included:

Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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Jake Stein
Jake Stein
CEO at Stitch | 16 upvotes 83.7K views
atStitchStitch
Clojure
Clojure
MySQL
MySQL
PostgreSQL
PostgreSQL

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.

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Ganesa Vijayakumar
Ganesa Vijayakumar
Full Stack Coder | Module Lead | 15 upvotes 1M views
Codacy
Codacy
SonarQube
SonarQube
React
React
React Router
React Router
React Native
React Native
JavaScript
JavaScript
jQuery
jQuery
jQuery UI
jQuery UI
jQuery Mobile
jQuery Mobile
Bootstrap
Bootstrap
Java
Java
Node.js
Node.js
MySQL
MySQL
Hibernate
Hibernate
Heroku
Heroku
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
Solr
Solr
Elasticsearch
Elasticsearch
Amazon Route 53
Amazon Route 53
Microsoft Azure
Microsoft Azure
Amazon EC2 Container Service
Amazon EC2 Container Service
Apache Maven
Apache Maven
Git
Git
Docker
Docker

I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

As per my work experience and knowledge, I have chosen the followings stacks to this mission.

UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

Happy Coding! Suggestions are welcome! :)

Thanks, Ganesa

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Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 15 upvotes 439.3K views
atUber TechnologiesUber Technologies
PostgreSQL
PostgreSQL
MySQL
MySQL
Python
Python

Our most popular (& controversial!) article to date on the Uber Engineering blog in 3+ yrs. Why we moved from PostgreSQL to MySQL. In essence, it was due to a variety of limitations of Postgres at the time. Fun fact -- earlier in Uber's history we'd actually moved from MySQL to Postgres before switching back for good, & though we published the article in Summer 2016 we haven't looked back since:

The early architecture of Uber consisted of a monolithic backend application written in Python that used Postgres for data persistence. Since that time, the architecture of Uber has changed significantly, to a model of microservices and new data platforms. Specifically, in many of the cases where we previously used Postgres, we now use Schemaless, a novel database sharding layer built on top of MySQL (https://eng.uber.com/schemaless-part-one/). In this article, we鈥檒l explore some of the drawbacks we found with Postgres and explain the decision to build Schemaless and other backend services on top of MySQL:

https://eng.uber.com/mysql-migration/

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MySQL Alternatives & Comparisons

What are some alternatives to MySQL?
PostgreSQL
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.
Oracle
Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
MariaDB
Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Microsoft SQL Server
Microsoft庐 SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
See all alternatives

MySQL's Followers
29303 developers follow MySQL to keep up with related blogs and decisions.
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Raja Prabhu
Steeve Luis Angel Torres Agustin