SQL, or Structured Query Language, is a programming language used for working with relational databases. SQL can be used to create and update data tables and query them to gather information from the data. Notably, SQL is used for relational data. That is, data points that are related to one another somehow. For example, if you have data about ten students and their grade levels, each student’s grade level is related to that student. To learn more about this language, check out our designated subject page.
In this post we’ll be exploring three technologies related to SQL – NoSQL, MySQL, and PostgreSQL. Each of these is a different type of technology with its own use cases, which we’ll explore below.
What is MySQL?
MySQL is a relational database management system developed by Oracle. It is a software tool that allows users to implement, manage, and query a database. While SQL is the language used to query and manipulate the data, MySQL is the software that helps house and organize the data.
SQL is a coding language that anyone can write, but MySQL is a software product that must be downloaded. The upsides of using the product is that it is maintained and updated regularly and users can access product support when something goes wrong.
What is PostgreSQL?
PostgreSQL is another type of relational database management system. Like MySQL, it is updated frequently and has a robust community of developers who can help troubleshoot issues. Like MySQL, users also use SQL programming when working in PostgreSQL.
PostgreSQL is more advanced than MySQL. It allows for more functionality such as additional data types and analytics functions. It also allows for a high volume of both reads and rights. For these reasons, PostgreSQLis favored for enterprise-scale applications. For smaller databases or individual projects, users often favor MySQL for its simplicity and ease of use.
What is NoSQL?
Counterintuitively, or intuitively depending on how you look at it, NoSQL is the opposite of SQL. NoSQL is an adjective to describe any databases that do not use SQL, that is any non-relational databases. People use the term “NoSQL” to mean either “Non-SQL” or “Not only SQL.”
The key element of NoSQL databases is that they are unstructured, whereas SQL databases are structured. NoSQL databases can be implemented in an endless number of ways depending on the programmer’s requirements. Four major types of NoSQL databases are:
- Document Databases – Data is stored as pairs of fields and values within documents.
- Key-Value Databases – Data is stored as sets of keys and values.
- Wide-Column Stores – Data is stored in rows and columns.
- Graph Databases – Data is organized into nodes (that hold identifying information) and edges (that hold information about how the nodes connect).
While NoSQL databases may not be the first pick for storing relational data (EG data for many different health metrics recorded about a set of patients), it is highly useful for other kinds of data because of its flexibility and ability to be queried very quickly. One of the most popular NoSQL databases that you may have heard of is MongoDB.
To summarize, SQL is a structured query language, used to work with relational databases. Relational databases are databases that house data points that are related to one another in some way. For example, data gathered about people is usually relational data; a person’s name, age, and zip code are all related to that person.
MySQL and PostgreSQL are two database management systems that users can download to help store and implement databases, using the SQL language. MySQL is a simpler software, while PostgreSQL is more advanced.
Finally, NoSQL refers to any non-SQL database. That is, a database that is unstructured and does not hold relational data. NoSQL databases, like MongoDB, are flexible and can be queried very quickly.
Learn more about SQL on our SQL subject page!