Relational databases and SQL were invented in the 1970s and continue to be dominant in the data world today, thanks to their various strengths such as relational calculus, consistent data, and logical data representation. However, the real success of relational databases can be attributed to two practical considerations: momentum and the power of the SQL query language.
“NoSQL” technology initially seemed to challenge these strengths, but it has gained momentum and is now providing the familiarity and power of SQL in its own unique way.
The Power of SQL
SQL, a declarative language for working with data, has revolutionized how we interact with databases. Without SQL, working with data would require specifying each step imperatively, resulting in verbose instructions for matching, grouping, projecting, and sorting data. In contrast, SQL queries allow us to simply specify what data we want, leaving the how-to details to the database. This leads to an easier-to-read and write language, standardized across relational databases, which contributes to their dominance.
The Limits of Relational Databases
Despite their success, relational databases have limitations, particularly when dealing with the scale of the internet. To handle more significant workloads, traditional relational servers need to be vertically scaled, meaning bigger and faster servers are required. However, this approach becomes impractical and costly for massive web companies like Amazon and Google. As a result, these companies turned to a new approach called NoSQL, where databases are horizontally scaled by joining multiple servers over a network.
The Rise of NoSQL
The NoSQL market experienced significant growth in recent years, outpacing the growth of relational databases. NoSQL gained popularity due to its suitability for horizontal scaling, which aligns with the needs of large-scale Internet services adopting a microservices architecture.
Challenges with NoSQL
While NoSQL and microservices provide scalability benefits, they also introduce new challenges. With each microservice having its own domain of data, data becomes distributed across different…