Relational Database

Data Storage and Sources
Updated on:
July 11, 2024

What is a relational database?

A relational database is a database structured to recognize relations between stored items of information. Data is stored in tables containing rows and columns, with rows representing records and columns representing attributes. Tables can be linked or related based on common attributes, enabling powerful and flexible ways to query for specific information.

The relational model defines strict rules governing these relations, allowing sophisticated querying and administration. It enforces integrity constraints to ensure accuracy and consistency of data. The relational structure enables changing schema without needing to reorganize underlying data storage. A language like SQL is used to define and manipulate the database. Robust relational databases are the predominant database technology used in modern applications.

Relational databases excel at complex query performance and strong consistency guarantees. Other database models like document stores and graph databases are better suited for specific access patterns involving unstructured or highly interconnected data.

What does it do/how does it work?

A relational database allows defining multiple interlinked tables each composed of rows and columns. Rows represent data records like customers or products. Columns define attributes like name, age, price. Relationships between tables are defined using primary keys and foreign keys.

Sophisticated querying using languages like SQL allows retrieving precise records or aggregated statistics by selecting, joining, grouping and filtering across multiple tables using both attributes and relationships. ACID properties ensure correctness of operations on the data.

Why is it important? Where is it used?

The robustness, flexibility and power of querying and managing data in relational databases make them a standard for business applications, CRMs, ERPs across domains. Joining related data, complex analytics, and ensuring integrity constraints are supported efficiently.

Used everywhere from mainframe billing systems to tiny SaaS apps, relational databases power much of the modern digital economy by providing the backbone for securely storing and accessing essential business data.


How are relational databases different from other database models?

Unlike other databases, relational databases are defined by formal relational algebra underpinning robust information storage and retrieval based on identifying and manipulating relations between entities.

  • Formal relational data model with relations between tables.
  • Schema defining tables, columns, datatypes, constraints.
  • ACID properties and transactions on the data.
  • Querying via languages like SQL operating across relations.
  • Mature technology with sophisticated administration.

When should you use a relational database?

Relational databases excel at complex querying across normalized datasets and ensuring data integrity, ideal for:

  • Transactional systems needing ACID guarantees.
  • Applications requiring complex business analytics.
  • Advanced data administration with huge amounts of records.
  • Legacy systems involving joined business data.
  • Scenarios where flexibility of schemas and queries is critical.

What are some key challenges with relational databases?

However, relational databases also come with tradeoffs around scalability, flexibility, and technology lock-in:

  • Join-intensive workloads affecting performance at scale.
  • Schema migrations requiring altering table structures.
  • Scaling across distributed infrastructure.
  • Vendor dependencies and proprietary extensions.
  • Specialized skillsets needed for administration.
  • Integrating legacy systems with modern data platforms.

What are some popular relational database technologies?

Some widely used relational database platforms and implementations include:

  • Oracle Database - Flagship relational database from Oracle.
  • MySQL - Popular open source relational database.
  • Microsoft SQL Server - RDBMS from Microsoft targeting enterprises.
  • PostgreSQL - Advanced open source object-relational database.
  • IBM Db2 - IBM's relational database software for high scalability.
  • MariaDB - Open source fork of MySQL relational database.
  • Amazon RDS - Managed relational databases on AWS.
  • SQLite - Self-contained, file-based relational database engine.

While SQL syntax is standardized, most major database vendors have their own proprietary extensions, optimizations, plug-ins and features. Evaluating specific application requirements and vendor offerings is recommended when choosing a relational database.


Related Entries

Document Store

Document store database manages collections of JSON, XML, or other hierarchical document formats, providing querying and indexing on document contents.

Graph Database

A graph database stores data in a graph structure with nodes, edges and properties to represent and query relationships between connected data entities.

SQL Compatibility

SQL compatibility refers to the degree to which a database or analytics system supports the SQL query language standard, enabling the use of standard SQL syntax and features.


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