What is SQL? Introduction to Structured Query Language

SQL can be used to create relational databases and perform an array of operations on existing databases, including data queries. The language is part of the standard repertoire of web developers, data analysts and researchers. But compared to other programming languages, SQL is special. We’ll explain the features of the language.

What exactly is SQL?

SQL is the ‘Structured Query Language’. It can be used to make queries to databases that contain structured or relational data. The language is based on ‘relational algebra’. This is a mathematical theory for structuring data and calculating the results of queries. Many of the special features of SQL as a programming language are derived from this mathematical basis. Developed in the mid-1970s, SQL is now considered the standard programming language for database applications.

An important detail about SQL is that it is a pure query or programming language, not a comprehensive database management system (DBMS). Some popular DBMSs that implement SQL are MySQL, Oracle SQL and SQLite. However, these DBMSs mostly use dialects of SQL, which may have additional and/or different commands.

SQL as a domain-specific and declarative language

Compared to most established programming languages, SQL is special because it is a domain-specific language (DSL). In contrast to the General Purpose Languages (GPLs), which are suitable for use in many different applications, SQL can only be used for one thing, databases.

SQL is also a declarative programming language. This means that the programmer enters a desired result as a command and the system ensures that this result is achieved. This is in contrast to imperative programming, in which the individual steps to achieve the goals are explicitly defined in the code.

What is SQL used for?

SQL serves as an interface for interacting with relational database management systems (RDBMS). A relational database can be thought of as a table in which each row entry has a predetermined set of attributes populated with values. The SQL code can either be entered by humans via a text-based interface or integrated into API accesses.

Advantages and disadvantages of SQL

Advantages of SQL

The biggest advantage of SQL lies in the high profile and widespread use of the technology. Since its origin in the 1970s, SQL has been the industry standard for database applications. This makes it relatively easy to find experienced SQL programmers, as well as interfaces with other common technologies and languages.

Moreover, SQL has become the industry standard for a reason. The language is based on a robust mathematical foundation that allows for optimal data storage. However, relational databases require a solid understanding of the technology and theory, as well as skill and planning in modelling. But a well-designed database schema makes it possible to gain new insights from the data through appropriate queries.

Disadvantages of SQL

One disadvantage of SQL and relational databases in general is the high complexity of the technology. SQL comprises hundreds of commands and clauses, which represent a major challenge for newcomers. Many of these are implementation-specific, making things even more challenging again.

In addition, the structure of a relational database requires a number of assumptions about the data to be stored. These serve to ensure the quality of the stored data, but also entail a number of limitations that can cause permanent problems if the schema is poorly designed. Changes to the schema during operation can pose a serious challenge. In addition to this lack of flexibility, it is usually very challenging to distribute an SQL database geographically. Optimising the performance of a database through decentralisation is, therefore, anything but simple.

A final disadvantage of SQL is its incompatibility with the widely used object-oriented programming, which is becoming increasingly relevant. In object-oriented programming, data and ‘behaviour’ (methods) are encapsulated in objects. Data and methods are inherited through class hierarchies. The relational approach is fundamentally different, as data can be distributed across several tables. In addition, it is impossible to model the behaviour of an object. For this reason, objects cannot be transferred 1:1 to relational database structures.

Alternatives to SQL

As SQL was invented at the beginning of the digital revolution, the language has not lost its relevance. However, some alternative schemas have since emerged that may be more suitable for some applications.

Object-relational database management systems

Object-relational database management systems (ORDBMS) such as PostgreSQL use SQL as a query language, but also support core concepts of object-oriented programming. Object hierarchies, inheritance and object behaviour can be used without the use of object-relational mapping (ORM). User-defined and composite data types in particular reduce the complexity of schemas and queries.

NoSQL

SQL-based DBMSs are primarily intended for storing structured data, but not all data follows a fixed schema. This is where NoSQL databases come into play. The term NoSQL refers to a family of non-relational DBMS. Instead of modelling data as fields in a table, various other approaches are used.

A popular approach is the document-based storage of data. This works by storing data in individual documents rather than storing it in a table. One advantage of the document-based approach is that the data can be self-writing. This means that the schema of the data is determined by the individual document, not by the database, meaning that data entries can follow different schemas.

NoSQL solutions are usually less complex and offer advantages in terms of scaling and performance optimisation. Furthermore, it is usually easier to change the schema during operation or to store data flexibly. On the other hand, there may be fewer guarantees with regard to the quality of the data.