Anyone who is interested in learning data science must be well-versed in SQL (Structured Query Language) databases. You must be aware of the best SQL databases if you intend to pursue a specialization in this area or a certification in it. In the modern world, data acquired and held by businesses, governments, and organizations is the primary means of generating income for both the public and private sectors.

One of the most in-demand skills in the data science profession is proficiency in the SQL programming language, which consistently ranks at the top of charts and rankings in the sector. Because so much of the information and data we share online is kept in SQL databases and management systems, the popularity of this language is directly related to how commonplace SQL databases are among businesses and computers. There are various database management systems that are helpful to the area of data science through this understanding of SQL as a language that can be utilized to work with relational databases.

The top SQL databases and examples of how students and professionals can utilize them for data science projects and portfolios are provided in the list below.

A relational database that is generally compatible with the SQL programming language is known as a SQL database. You can compare datasets inside either relational database systems or SQL databases thanks to their structure. It is simple to perform these comparisons within the dataset and to keep data within tables because these systems are often designed in a rows-and-column manner. These tables can be used to manipulate and retrieve information and data as database objects. Relational databases are thus centered on structured data that can be arranged, categorized, and sorted according to this system and the data kinds and objects contained inside it.

While SQL is known as a programming language, as a “structured query language” the primary use of SQL is the manipulation and management of data. Much of the education around SQL includes instruction on writing queries for relational databases. Queries are used to search through a dataset, making it easier to clean and organize it. Through querying, data scientists are able to filter, sort, and group data as well as return descriptive statistics. As the primary use of SQL databases, querying can also be used as a form of data mining or exploratory analysis, which ensures that you are familiar with the dataset by examining what it contains and what might be missing.

Once data is imported into a SQL database, data scientists are also able to edit, modify, and/or update database objects. For example, SQL databases allow you to delete records or other aspects of the dataset from the database with relative ease. This is especially useful when collecting and storing data over a period of time, or when there are any changes to the metadata within a dataset or the understanding of that data. Instead of having to manually update these records (which might be a necessity if the data was stored in a file system), SQL databases allow for a greater sense of flow and transformation of information and data.

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There are a variety of SQL-compatible database management systems. The most well-known SQL databases are included in the list below, with an emphasis on free and open-source data science applications that can be used to clean, arrange, and organize datasets.

1. PostgreSQL

Another open-source SQL database, PostgreSQL is a relational database system that is known for its high level of performance and capacity to work with large stores of data. Prioritizing security and integrity, PostgreSQL includes several features which reflect the responsiveness of this software and the community which contributes to it, to solving some of the major challenges and concerns within database design. A versatile and scalable system, this database also offers the unique feature of not only being programmable with SQL but with a variety of programming languages, such as Python, in addition to being able to handle both structured and unstructured data.

2. Microsoft SQL Server

Included as one of many data science tools offered by Microsoft, SQL Server is well known within the data science industry and is highly compatible with Azure and Microsoft’s business intelligence (BI) products. Geared towards big data projects, this database is focused on offering speed and efficiency to data scientists that need to query large datasets. While most databases focus on the management of structured and relational datasets, SQL Server is also capable of handling multiple data types, including non-relational and unstructured data.

3. MySQL

Viewed as one of the most popular open-source SQL databases, MySQL offers several services for individuals as well as businesses as a product of Oracle database services. Students and professionals that want to receive training in MySQL can also take part in the MySQL Certification Program, which offers education for developers and database administrators. MySQL also prides itself on being the database service of choice for multiple high profile corporations and technology platforms, such as YouTube, Uber, and PayPal, therefore certification in this database system is especially useful when pursuing employment at a company that uses SQL databases.

4. SQLite

Described as a database engine, SQLite stands out from other SQL databases in that it does not have a separate server in which to store the information and data of users. Acting as a library, data scientists can use SQLite to easily migrate stores of data from one system to another because it is both compact and mobile. SQLite is generally known as a database that is used by software engineers and developers that are working with mobile applications and cellphones.

5. IBM Db2 Database

Offering several database services and programs, IBM is well respected within the world of relational database management systems. With several platforms and editions, the Db2 databases are compatible with multiple operating systems and offer services that specialize in the safety and security of information and data. As a SQL database, IBM Db2 is also a cloud-based software that makes it easy to access your data when using different computers and working in a variety of environments.