The biggest uses of Structured Query Language (SQL) today have to do with using a long-established conventional language for relational database with newly emerging enterprise IT environments, like cloud-native systems, virtual networks, etc.
Essentially, SQL is used to retrieve data or otherwise interface with a relational database. As a standard going back to the 1970s, SQL is a popular way to get information out of relational database systems.
Relational databases are set up with a particular structure — each record has a series of keys that are linked to one another in consistent ways, and placed in a "table" represented visually in a grid.
The SQL language is written to comb the contents of tables in a conventional database. SQL is widely used in business and in other types of database administration.
It is often the default tool for “operating” on the conventional database, to alter tabled data, retrieve data or otherwise manipulate an existing data set.
So, part of the reason that SQL is still so popular so many years after its creation is its ubiquity in current IT systems. The environments may have changed a lot, but the relational database technologies have changed more slowly.
Another major part of SQL’s prime use today is in its simplicity. Simple SQL commands like SELECT, ORDER BY and INSERT (all of which are typically rendered in all capital letters) help administrators to route data in and out of a database table.
This goes on over all sorts of platforms, and is a major part of delivering data results in today’s cloud and hybrid distributed systems. SQL remains one of the least “dreaded” languages according to developer surveys in recent years.
Because of the fairly straightforward syntax and ease of use, administrators can then focus on the theory of database construction and the logistical aspect of getting data into and out of systems.
The concept is that data that is not tabled in a relational database may not need SQL as a query language. So the biggest uses of SQL are in a spectrum that might be called “smaller” database systems.
Another way to explain this is that SQL does not “scale infinitely.” So by that principle, the SQL is used for traditional DB systems and other methods are used for larger NoSQL database systems where checks on data are not strictly enforced. (Also read: What is the difference between a NoSQL database and a traditional database management system?)
However, NoSQL has not led SQL itself to become obsolete. On the contrary, those same basic mathematical principles and syntax methods that have always driven SQL in the days of bare-metal servers are still applied to relational database systems running in containers or virtual machines or what-have-you.
The simplest way to explain this is that SQL DB systems remain popular “legacy” components in enterprise IT, and that they are now often supported differently, whether that’s through the cloud, through SaaS models, or otherwise.
For example: AWS has come up with AWS Lambda, a service for serverless computing. Experts online talk about the feasibility of developing a “SQL to Lambda” to use a radically new method to interact with relational database in traditional ways.
By using the AWS SDK to invoke Lambda functions, and passing data in the form of JSON strings, these systems exemplify how today’s modern SQL utility can work as a versatile component of cutting-edge architectures.