science

SQL

SQL is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand SQL rather than just read about it. In short: Structured Query Language (SQL) (pronounced S-Q-L; or alternatively as "sequel") is a domain-specific language used to manage data, especially in a relational database management system (RDBMS). It is particularly useful in handling structured data, i.e., data incorporating relations among entities and variables.

Key takeaways

SQL belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect SQL to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of SQL from memory before moving on to harder problems.

Reference excerpt

Structured Query Language (SQL) (pronounced S-Q-L; or alternatively as "sequel") is a domain-specific language used to manage data, especially in a relational database management system (RDBMS). It is particularly useful in handling structured data, i.e., data incorporating relations among entities and variables. Introduced in the 1970s, SQL offered two main advantages over older read–write APIs such as ISAM or VSAM. Firstly, it introduced the concept of accessing many records with one single command. Secondly, it eliminates the need to specify how to reach a record, i.e., with or without an index. Originally based upon relational algebra and tuple relational calculus, SQL consists of many types of statements, which may be informally classed as sublanguages, commonly: data query language (DQL), data definition language (DDL), data control language (DCL), and data manipulation language (DML). The scope of SQL includes data query, data manipulation (insert, update, and delete), data definition (schema creation and modification), and data access control. Although SQL is essentially a declarative language (4GL), it also includes procedural elements. SQL was one of the first commercial languages to use Edgar F. Codd's relational model. The model was described in his influential 1970 paper, "A Relational Model of Data for Large Shared Data Banks". Despite not entirely adhering to the relational model as described by Codd, SQL became the most widely used database language. SQL became a standard of the American National Standards Institute (ANSI) in 1986 and of the International Organization for Standardization (ISO) in 1987. Since then, the standard has been revised multiple times to include a larger set of features and incorporate common extensions. Despite the existence of standards, virtually no implementations in existence adhere to it fully, and most SQL code requires at least some changes before being ported to different database systems.

History SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd in the early 1970s. This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San Jose Research Laboratory had developed during the 1970s. Chamberlin and Boyce's first attempt at a relational database language was SQUARE (Specifying Queries in A Relational Environment), but it was difficult to use due to subscript/superscript notation. After moving to the San Jose Research Laboratory in 1973, they began work on a sequel to SQUARE. The original name SEQUEL, which is widely regarded as a pun on QUEL, the query language of Ingres, was later changed to SQL (dropping the vowels) because "SEQUEL" was a trademark of the UK-based Hawker Siddeley Dynamics Engineering Limited company. The label SQL later became the acronym for Structured Query Language. After testing SQL at customer test sites to determine the usefulness and practicality of the system, IBM began developing commercial products based on their System R prototype, including System/38, SQL/DS, and IBM Db2, which were commercially available in 1979, 1981, and 1983, respectively. IBM's endorsement caused the industry to move to SQL from alternatives like QUEL. In the late 1970s, Relational Software, Inc. (now Oracle Corporation) saw the potential of the concepts described by Codd, Chamberlin, and Boyce, and developed their own SQL-based RDBMS with aspirations of selling it to the U.S. Navy, Central Intelligence Agency, and other U.S. government agencies. In June 1979, Relational Software introduced one of the first commercially available implementations of SQL, Oracle V2 (Version2) for VAX computers. By 1986, ANSI and ISO standard groups officially adopted the standard "Database Language SQL" language definition. New versions of the standard were published in 1989, 1992, 1996, 1999, 2003, 2006, 2008, 2011, 2016 and, most recently, 2023.

Interoperability and standardization

Overview SQL implementations are incompatible between vendors and do not necessarily completely follow standards. In particular, date and time syntax, string concatenation, NULLs, and comparison case sensitivity vary from vendor to vendor. PostgreSQL and Mimer SQL strive for standards compliance, though PostgreSQL does not adhere to the standard in all cases. For example, the folding of unquoted names to lower case in PostgreSQL is incompatible with the SQL standard, which says that unquoted names should be folded to upper case. Thus, according to the standard, Foo should be equivalent to FOO, not foo. Popular implementations of SQL commonly omit support for basic features of Standard SQL, such as the DATE or TIME data types. The most obvious such examples, and incidentally the most popular commercial and proprietary SQL DBMSs, are Oracle (whose DATE behaves as DATETIME, and lacks a TIME type) and MS SQL Server (before the 2008 version). As a result, SQL code can rarely be ported between database systems without modifications.

Reasons for incompatibility Several reasons for the lack of portability between database systems include:

The complexity and size of the SQL standard means that most implementers do not support the entire standard. The SQL standard does not specify the database behavior in some important areas (e.g., indices, file storage), leaving implementations to decide how to behave. The SQL standard defers some decisions to individual implementations, such as how to name a results column that was not named explicitly. The SQL standard precisely specifies the syntax that a conforming database system must implement. However, the standard's specification of the semantics of language constructs is less well-defined, leading to ambiguity. Many database vendors have large existing customer bases; where the newer version of the SQL standard conflicts with the prior behavior of the vendor's database, the vendor may be unwilling to break backward compatibility. Little commercial incentive exists for vendors to make changing database suppliers easier (see vendor lock-in). Users evaluating database software tend to place other factors such as performance higher in their priorities than standards conformance.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with SQL

Start with the simplest possible case. Write down what SQL claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to SQL before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about SQL ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of SQL

In research: SQL appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses SQL in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: SQL is common in secondary-school and first-year university syllabi. It links to neighbouring topics Data-centric programming languages, Data modeling languages, Database management systems, so understanding it makes those chapters shorter.
In everyday life: Look for SQL outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study SQL in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what SQL means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain SQL out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is SQL in simple terms?

Why does SQL matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study SQL?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on SQL.

SQL