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A Brief History of SQL - Origins and Expansion

Published: 9th February, 2024

Meghdeep Patnaik

Head - Content and Social Media at almaBetter

In this article, we dive into the history of SQL, its advantages, origins, expansion, standardization, commercialization, diversification and more. Read on.

The advantages of SQL (Structured Query Language) are numerous when it comes to managing and manipulating data within relational database systems. Its declarative nature allows users to specify what data they need without detailing how to retrieve it, promoting simplicity and abstraction. SQL enables efficient data retrieval and manipulation operations, facilitating complex queries and analytics tasks. Moreover, its standardized syntax ensures portability across different database platforms, enhancing interoperability and scalability. With features like transaction management, data integrity constraints, and user access controls, SQL ensures data consistency, security, and reliability. Overall, SQL empowers organizations to effectively organize, query, and derive insights from their data, driving informed decision-making and business success.

In the vast landscape of data management and database systems, SQL stands as a cornerstone, enabling users to interact with databases efficiently. The evolution of SQL is rich with innovations, advancements, and milestones that have shaped its evolution into the ubiquitous language it is today. Let's embark on a journey through time to explore the fascinating history of SQL.

Origins and Early Development

1. Birth of Relational Model:

SQL traces its roots back to the early 1970s when IBM researcher Edgar F. Codd proposed the relational model for database management. Codd's groundbreaking paper, "A Relational Model of Data for Large Shared Data Banks," laid the foundation for organizing and querying data in a structured manner.


In the mid-1970s, IBM developed SEQUEL (Structured English Query Language) as a query language for interacting with its System R database management system. SEQUEL aimed to provide a user-friendly interface for querying relational databases using English-like commands.

Standardization and Commercialization

1. SQL-86:

As relational database systems gained traction in the industry, efforts were made to standardize the query language. In 1986, ANSI (American National Standards Institute) published the first SQL standard, known as SQL-86. This standard laid the groundwork for subsequent versions of SQL.

2. SQL-89 and SQL-92:

Building upon the foundation of SQL-86, ANSI released SQL-89 and SQL-92 standards, which introduced significant enhancements and refinements to the language syntax and functionality. These standards solidified SQL as the de facto language for relational databases.

Expansion and Diversification

1. Commercial Database Systems:

The 1990s witnessed the rise of commercial database management systems (DBMS) from vendors like Oracle, Microsoft, and IBM. These systems implemented SQL as the primary interface for interacting with databases, further popularizing the language.

2. SQL-99 and Beyond:

In 1999, ANSI published the SQL-99 standard, also known as SQL3, which introduced advanced features such as support for object-oriented programming, XML data handling, and recursive queries. Subsequent versions, including SQL:2003, SQL:2008, and SQL:2016, continued to enhance SQL's capabilities and address emerging trends in data management.

Technological Advancements

1. Internet and Web Development:

The proliferation of the Internet and the emergence of web applications in the late 20th century drove the need for database-driven websites and online services. SQL became integral to web development, enabling developers to store, retrieve, and manipulate data efficiently.

2. Big Data and Analytics:

In the 21st century, the explosion of data generated by several sources, including social media, IoT devices, and sensors, propelled the demand for advanced data analytics and processing. SQL found new applications in big data platforms like Hadoop and Spark, enabling analysts to query and analyze massive datasets.

Modern Landscape and Future Directions

1. NoSQL and NewSQL:

While SQL remains dominant in traditional relational databases, the advent of NoSQL (Not Only SQL) databases introduced alternative approaches to data management, catering to specific use cases such as scalability and flexibility. NewSQL databases aim to combine the benefits of traditional SQL databases with the scalability of NoSQL solutions.

2. Cloud Computing and Serverless Architectures:

The shift towards cloud computing and serverless architectures has reshaped the database landscape, with managed database services offering scalable, cost-effective solutions for organizations. SQL continues to play a crucial role in these environments, providing familiar querying capabilities for cloud-native applications.


From its humble beginnings as a research project to its ubiquitous presence in modern database systems, SQL history reflects the evolution of data management and technology. As firms continue to embrace digital transformation and harness the power of data, SQL remains a vital tool for querying, analyzing, and managing information effectively. To start your journey towards mastering SQL, you can explore our easy-to-under SQL tutorial.

As we look to the future, SQL will continue to evolve alongside emerging technologies such as artificial intelligence, machine learning, and edge computing, adapting to new challenges and opportunities in the ever-changing landscape of data-driven innovation.

In conclusion, the history of SQL is not just a chronicle of technological advancements but a testament to the enduring relevance and versatility of a language that has revolutionized the way we interact with data. As we celebrate its past achievements, we eagerly await the exciting possibilities that lie ahead in the ongoing saga of SQL's evolution.

If you are interested in furthering your career in the Data Science domain, pursuing a comprehensive Data Science certification is the best bet in the current tech market.

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