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What is Database

Database Definition:

A database is an organised collection of data stored electronically to make it easier to query, manage and update. It is administered through a database management system or DBMS, which controls operations such as reading, writing, security and data integrity.

The way data is organised depends on the model used. In a relational database, for example, information is arranged in tables made up of rows and columns and can be connected through keys. A telephone directory is a simple example: each record may contain fields such as name, address and telephone number, related to the concept of NAP.

What databases are for

Databases provide a structure for working with information in applications, web services and business processes. Their common functions include:

  • Information storage: They retain structured or semi-structured data to facilitate its management.
  • Data management: They allow information to be created, queried, updated and deleted according to the system’s rules.
  • Fast retrieval: They use queries and indexes to locate records without reviewing the entire data set.
  • Data analysis: They provide information for examining trends, producing reports and supporting decisions.
  • Information security: They can include access controls, permissions, encryption and audit mechanisms depending on the technology and configuration.
  • Application integration: They support information exchange between applications and services through connectors, queries or APIs.
  • Transaction support: They can execute operations while maintaining integrity and consistency properties, particularly in financial and ecommerce systems.
  • Scalability: They support different strategies for responding to growth in data volume, queries or users.
  • Process automation: They allow tasks such as backups, maintenance, report generation and record updates to be scheduled.

Classification of databases

The same database may belong to several categories because different classification criteria can be applied.

According to data variability

  • Static: They retain historical information or data sets that change infrequently and are used mainly for queries and analysis.
  • Dynamic: They support frequent additions, modifications and deletions as new operations occur.

According to content

  • Bibliographic: They contain references and descriptions of documents, such as author, title or publication date.
  • Full-text: They store the complete content of documents to support retrieval and queries.
  • Directories: They organise data about people, companies, resources or locations, such as telephone directories and web directories.
  • Chemical or biological: They contain specialised scientific information, such as molecular structures or genetic sequences.

According to the data model

  • Relational: They organise information in related tables and are commonly queried with SQL. MySQL, PostgreSQL, Oracle Database and Microsoft SQL Server are examples.
  • NoSQL: They cover non-relational models such as document, key-value, wide-column and graph databases. MongoDB, Redis, Apache Cassandra and Neo4j represent different families.

According to access and distribution

  • Centralised: They keep data under the control of a main system or location, although it may be queried from other devices.
  • Distributed: They spread data or replicas across several coordinated nodes or locations.

According to purpose

  • OLTP, online transaction processing: They are optimised for many short operations, such as orders, payments or inventory updates.
  • OLAP, online analytical processing: They are designed for complex queries, aggregations and analysis of large data sets.

According to the licence model

  • Open source: Their open-source code can be used, studied and modified under the applicable licence. PostgreSQL, MySQL and MariaDB are examples.
  • Proprietary: They are distributed by a company under conditions that restrict access to or modification of the source code. Oracle Database and Microsoft SQL Server have proprietary editions.

Most widely used database technologies

Technologies are selected according to the data model, consistency requirements, workload, availability and query needs. Well-known examples include:

  • MySQL: An open-source relational database management system used in web applications and business systems.
  • PostgreSQL: An open-source relational system with advanced features, extensibility and support for ACID transactions.
  • Oracle Database: A proprietary relational system used, among other purposes, for enterprise applications requiring advanced availability, security and administration features.
  • Microsoft SQL Server: Microsoft’s relational system, integrating administration, analytics and reporting tools.
  • MongoDB: A document database that stores records in flexible documents and supports horizontal scaling.
  • Redis: An in-memory data store used for caching, sessions, queues and other operations requiring low latency.
  • Apache Cassandra: A distributed wide-column database designed to operate across multiple nodes and maintain high availability.
  • Elasticsearch: A distributed search and analytics engine that stores indexed documents. It can complement an operational database when text search and fast aggregations are required.

Related Terms