What is MySQL? Everything You Need to Know
MySQL is one of the most recognizable technologies in the modern big data ecosystem. Often called the most popular database and currently enjoying widespread, effective use regardless of industry, it’s clear that anyone involved with enterprise data or general IT should at least aim for a basic familiarity of MySQL.
With MySQL, even those new to relational systems can immediately build fast, powerful, and secure data storage systems. MySQL’s programmatic syntax and interfaces are also perfect gateways into the wide world of other popular query languages and structured data stores.
What is MySQL?
MySQL is a relational database management system (RDBMS) developed by Oracle that is based on structured query language (SQL).
A database is a structured collection of data. It may be anything from a simple shopping list to a picture gallery or a place to hold the vast amounts of information in a corporate network. In particular, a relational database is a digital store collecting data and organizing it according to the relational model. In this model, tables consist of rows and columns, and relationships between data elements all follow a strict logical structure. An RDBMS is simply the set of software tools used to actually implement, manage, and query such a database.
MySQL is integral to many of the most popular software stacks for building and maintaining everything from customer-facing web applications to powerful, data-driven B2B services. Its open-source nature, stability, and rich feature set, paired with ongoing development and support from Oracle, have meant that internet-critical organizations such as Facebook, Flickr, Twitter, Wikipedia, and YouTube all employ MySQL backends.
|Current Developer||Oracle Corporation|
|Original Developer||MySQL AB (Then, briefly, Sun Microsystems)|
|Current Stable Release||8.0.16 (on April 25, 2019)|
|Original Release||May 23, 1995|
|License||GPLv2 (or proprietary)|
|Primary language||C and C++|
4 keys to understanding MySQL
Because MySQL enjoys the most widespread use in many industries, business users from new webmasters to experienced managers should strive to understand its main characteristics. Deciding whether to use this technology, and communicating about it effectively, starts with a review of MySQL’s basic availability, structure, philosophy, and usability.
MySQL is widely compatible
Though often associated with internet applications or web services, MySQL was designed to be extensively compatible with other technologies and architectures. The RDBMS runs on all major computing platforms, including Unix-based operating systems, such as the myriad Linux distributions or Mac OS, and Windows.
MySQL’s client-server architecture means it can support a variety of backends, as well as different programming interfaces. Data can be directly migrated from MySQL to its forks (e.g. MariaDB), as well as most other RDBMSs thanks to architectural and language similarities.
Established Oracle and third-party migration tools further allow MySQL to move data to and from a vast set of general storage systems, whether these are designed to be on-premises or cloud-based. MySQL can be deployed in virtualized environments, distributed or centralized, and even exists as portable standalone libraries for learning purposes, testing, or small applications.
MySQL’s wide compatibility with all these other systems and software makes it a particularly practical choice of RDBMS in most situations.
MySQL databases are relational
The primary factor differentiating relational databases from other digital storage lies in how data is organized at a high level. Databases like MySQL contain records in multiple, separate, and highly codified tables, as opposed to a single all-encompassing repository, or collections of semi- or unstructured documents.
This allows RDBMSs to better optimize actions like data retrieval, updating information, or more complex actions like aggregations. A logical model is defined over all of the contents of the database, describing for example the values allowed in individual columns, characteristics of tables and views, or how indices from two tables are related.
Relational models have remained popular for several reasons. They empower users with intuitive, declarative programming languages — essentially telling the database what result is wanted in language akin to, or at least comprehensible as, written english, instead of meticulously coding up each step of the procedure leading to that result. This moves a lot of the work into the RDBMS and SQL engines, better enforcing logical rules and saving valuable resources and manpower.
MySQL is open-source
Any individual or enterprise may freely use, modify, publish, and expand on Oracle’s open-source MySQL code base. The software is released under the GNU General Public License (GPL).
For MySQL code needing to be integrated or included in a commercial application (or if open-source software is not a priority), enterprises can purchase a commercially licensed version from Oracle.
Again, these options provide organizations with additional flexibility if deciding to work with MySQL. The public and community-based nature of open-source releases enriches MySQL’s documentation and online support culture, while also ensuring that sustained or newly-developed capabilities never stray too far from current user needs.
MySQL is easy to use
Though MySQL’s relational nature and the ensuing rigid storage structures might seem restrictive, the tabular paradigm is perhaps the most intuitive, and ultimately allows for greater usability.
In fact, MySQL makes many concessions to supporting the widest possible variety of data structures, from the standard but rich logical, numeric, alphanumeric, date, and time types, to more advanced JSON or geospatial data. Beyond mere data types and an expansive built-in feature set, the MySQL ecosystem also includes a variety of tools, easing everything from server management to reporting and data analysis.
Regardless of the RDBMS’s overarching architecture, users can invariably find a MySQL feature allowing them to model and codify data how they wish. MySQL remains one of the most straightforward database technologies to learn and use.
SQL vs. MySQL: What’s the difference?
The relational model was first delineated in a 1970 paper by Edgar F. Codd. One of the first commercial programming languages related to the model, SQL, was developed shortly after at IBM. For some time, SQL was the most widely used database language, adopted as an ANSI standard in 1986 and in ISO a year later.
SQL is composed of four sublanguages, each with a different scope.
- DQL: The data query language (DQL) is the most familiar and is used to run queries on databases and extract information from stored data. For example, selecting and returning the maximum value in a column.
- DDL: A data definition language (DDL) is used to codify a database’s particular structures and schemas. Creating a table or defining data types is an example.
- DCL: A data control language (DCL) defines access, authorizations, and permissions for users and processes accessing the database, including granting administrator privileges, or restricting users to read-only privileges only.
- DML: And finally, a data manipulation language (DML) is used to make modifications on existing components of a database, like inserting records, updating values in cells, or deleting data.
Swedish company MySQL AB first released MySQL in 1995. Like much of the database software which followed the initial rise of relational systems, MySQL is simply an extension of the original SQL standard, adding more features, support, procedural programming, control-flow mechanisms, and more.
The cloud and the future of MySQL
MySQL was originally envisioned to manage massive databases, faster than existing database software. Used in demanding operational, transactional, and production environments for decades, MySQL evolved alongside the move of computation and storage into the cloud.
Though typically installed on individual machines, MySQL now includes deep support for distributed applications and inclusion in most cloud data platforms.
Relative to many data storage and processing solutions on the market today, MySQL is an older technology, but it shows no signs of flagging in either popularity or utility. In fact, MySQL has enjoyed a recent resurgence over even more specialized modern storage systems, due to its speed, reliability, ease of use, and wide compatibility.
Getting started with MySQL
MySQL is a popular, time-tested, but also modern and fully-featured relational database management software. Businesses everywhere use it for mission-critical enterprise data storage, processing, as a backend to major customer-facing applications, and as part of powerful, established web software stacks.
Whether your business already uses MySQL or is planning new systems or migrations to this RDBMS, the importance of data integration cannot be overstated. Talend provides a comprehensive suite of apps for managing data ecosystems from end to end, allowing businesses to collect, transform, govern, and share fast and trusted data from any system. Try Talend Data Fabric today for a seamless data ecosystem.
Ready to get started with Talend?
More related articles
- What is Middleware? Technology’s Go-to Middleman
- What is Shadow IT? Definition, Risks, and Examples
- What is Serverless Architecture?
- What is SAP?
- What is ERP and Why Do You Need It?
- What is “The Data Vault” and why do we need it?
- What is a Data Lab?
- Understanding Cloud Storage
- What is a Legacy System?
- What is Data as a Service?
- What is a Data Mart?
- What is Data Processing?
- Understanding data mining: Techniques, applications, and tools
- What is Apache Hive?
- Data Munging: A Process Overview in Python
- What is a Data Source?
- Data Transformation Defined
- SQL vs NoSQL: Differences, Databases, and Decisions
- Data Modeling: Ensuring Data You Can Trust
- How modern data architecture drives real business results
- Data Gravity: What it Means for Your Data
- CRM Database: What it is and How to Make the Most of Yours
- Data Conversion 101: Improving Database Accuracy