What is SQL (structured query language)?
SQL (structured query language) is the standard language for managing and querying structured data in relational databases. As an internationally recognized standard, SQL enables databases to be created, queried, modified, and managed—and forms the technical foundation for business intelligence, data warehousing, and modern data analysis.
| Feature | Details |
| Category | Database language, IT infrastructure, data management |
| Area of application | Relational databases, business intelligence, data warehousing, reporting, data analysis |
| Typical use cases | Data queries, data maintenance, report generation, KPI modeling, ETL processes |
| Related terms | Relational database, data warehouse, ETL, MDX, OLAP, MySQL, PostgreSQL |
| Benefits | Consistent data, fast processing, security, scalability, cross-platform compatibility |
At a glance
Declarative language: SQL describes what should be queried—not how the database executes the query.
Enables access to structured data through commands such as SELECT, INSERT, UPDATE, and DELETE.
Forms the basis for data analysis, reporting, and data warehouse processes.
Supported by all leading relational database systems: MySQL, PostgreSQL, SQL Server, SAP HANA.
SQL definition
The abbreviation SQL stands for structured query language and refers to a standardized, internationally recognized query language for managing and processing data in relational database systems.
SQL can be used to create, modify, manage, and query databases. Typical applications include inserting new data, updating existing records, and deleting data that is no longer required. SQL can also be used to create complex queries for selectively filtering and analyzing information.
As a declarative language, SQL describes what a user wants to achieve—for example, which data is required—without specifying exactly how the database should perform the task. This makes SQL a key tool for business intelligence, data warehousing, and many applications involving large volumes of data and modern data analysis.
How does SQL work?
SQL processes database queries in several steps to ensure that data is stored, retrieved, or modified correctly, securely, and efficiently. Various components work closely together:
- Parser (syntax and access checks)
- Checks whether the user executing the query has the necessary permissions to perform the requested operation.
- Breaks the SQL statement down into individual elements (“tokenization”) and checks whether the syntax complies with the applicable rules.
- Relational engine (query optimization)
- Converts the validated statement into so-called bytecode.
- Creates an execution plan to read or modify data as efficiently as possible.
- Optimizes recurring queries and selects the fastest access method.
- Storage engine (physical data execution)
- Executes the execution plan: it reads data from disk or writes new information to the database.
- Permanently stores changes and returns the results to the requesting application.
What are the most important SQL commands?
There are various SQL commands for managing data in relational databases. Some of the most important include:
Data access and manipulation (DML)
- SELECT: Query data from one or more tables, e.g.: SELECT Name FROM Suppliers WHERE City = ‘Hamburg’
- INSERT: Insert new records into a table, e.g.: INSERT INTO Suppliers (Name, City) VALUES (‘Max Mustermann’, ‘Hamburg’)
- UPDATE: Modify existing records, e.g.: UPDATE Suppliers SET PhoneNumber = ‘new phone number’ WHERE Name = ‘Max Mustermann’
- DELETE: Delete records from a table, e.g.: DELETE FROM Suppliers WHERE City = ‘Leipzig’
Database structure (DDL)
- CREATE: Create new database objects, such as tables.
- ALTER TABLE: Modify the structure of database objects, e.g.: ALTER TABLE Suppliers ADD COLUMN ContractEnd DATE
- DROP: Delete database objects, e.g.: DROP TABLE Suppliers_Old
Access control (DCL)
- GRANT: Grant user permissions.
- REVOKE: Revoke user permissions.
Joining data
- JOIN: Combine data from multiple tables.
What are the advantages of SQL?
SQL is virtually indispensable when working with relational databases. Key advantages include:
Consistent data and complex analyses: SQL organizes data in tables with rows and columns. Relational links between tables, such as those based on primary and foreign keys, ensure data integrity and enable complex queries.
Fast processing: Indexes and optimization techniques ensure short response times, even with large volumes of data.
Security: Access controls and encryption protect against unauthorized access.
Compatibility: As a standardized language, SQL can be used across platforms, including in cloud and big data environments.
Scalability and open source: Many SQL systems are open source and can be adapted flexibly to growing data requirements.
What is the difference between SQL and MySQL?
SQL and MySQL have different roles in the world of databases: SQL is the language, while MySQL is a specific database management system.
| Feature | SQL | MySQL |
| What is it? | Standardized query language | Relational database management system (RDBMS) |
| Function | Defines how databases are structured and how data is processed | Software that executes SQL commands and stores data |
| Dependency | Independent of specific software | Uses SQL as its query language |
SQL is the standardized language for managing and querying relational databases. It defines how databases are structured and how data is processed, regardless of which software is used.
MySQL is a widely used relational database management system (RDBMS) that uses SQL commands to store, manage, and provide data. MySQL is open source, developed by Oracle, and can be installed on various operating systems or deployed in the cloud.
Language vs. system: SQL is a syntax and set of rules; MySQL is software that implements those rules.
Alternative systems: In addition to MySQL, other database systems use SQL, such as Microsoft SQL Server and PostgreSQL.
The difference between SQL and MySQL is therefore that SQL describes how databases are accessed, while MySQL is one of many software solutions that use SQL as a query language.
Bissantz and SQL
Bissantz’s DeltaMaster business intelligence software accesses relational databases that can be efficiently queried and analyzed using SQL.
SQL is not merely a means of querying data; it is the foundation for many central functions in the DeltaMaster environment. From KPI-based reports, dynamic dashboards, and automated analyses to KPI modeling, access to databases is almost always handled through SQL—whether through precomputed queries (views), dynamically generated statements, or integration into data warehouse architectures.
Bissantz aims to reduce SQL complexity through intelligent preprocessing and automated modeling. This enables business users to work with analytical functions without having to write SQL themselves, while power users and IT teams retain in-depth control over SQL.
Through its consistent support for relational systems such as Microsoft SQL Server, SAP HANA, Oracle, and PostgreSQL, DeltaMaster can be used in virtually any corporate environment—on-premises or in the cloud, optimized for SQL standardization and performance. Combined with intelligent visualizations such as Sparklines and Bissantz’Numbers, this creates a solution that ideally combines technology and user value.
FAQ – frequently asked questions
SQL is the language used to “talk” to a database. If a company wants to know which customers generated more than €10,000 in revenue last quarter, it can express that question in SQL—and the database provides the answer. SQL is designed so that users describe what they want, rather than how the database should calculate it.
SQL is a domain-specific language specialized in communicating with relational databases. Unlike general-purpose programming languages such as Python or Java, SQL does not describe algorithms or program flows but database operations. In practice, however, SQL is often combined with programming languages—for example, when Python scripts execute SQL queries to load data for analysis.
SQL is the query language for relational databases, optimized for transactions and structured tables. MDX (Multidimensional Expressions) is the query language for OLAP cubes, optimized for multidimensional analyses across hierarchies and dimensions. DeltaMaster uses both languages: SQL to access relational sources and MDX for multidimensional OLAP models.
No. Bissantz designed DeltaMaster so that business users can work with its analytical functions without any knowledge of SQL. SQL runs in the background—automatically generated, optimized, and executed. For IT teams and power users, however, DeltaMaster provides full transparency and control over SQL when deeper customization is required.
Summary
SQL is an indispensable foundation of modern data management and analysis. As a standardized, cross-platform language, it enables consistent, fast, and secure database operations—from simple queries to complex analyses in data warehouse architectures. Bissantz uses SQL as the technical foundation of DeltaMaster while ensuring that the complexity remains in the background: business users receive clear analyses and comprehensible visualizations without having to write a single line of SQL themselves.
Related terms – deepen your knowledge
Free of charge for you
Quickguide "Business Intelligence": download now!
