8 new languages ​​for querying data “beyond SQL”

Over the past 30 years, databases and SQL (Structured Query Language) have been used almost synonymously. To extract information from a database, anyone had to learn SQL, and anyone with an interest in databases or choosing to become a database administrator as a career had to master the complex syntax of SQL.
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SQL itself is an opportunity to think and code the old way, the way mainframe users did. Even while the whole world accepted lowercase letters, SQL users continued to use words like SELECT and WHERE. There are people on TikTok who mock it by asking why they always yell at it, but most SQL users don’t mind the mockery. If the people who handled punch cards in ties and short-sleeved shirts used all capital letters without any problem, the current telecommuters wearing teddy bear print pajamas can use them without any problem.

However, SQL’s position in the data retrieval area is gradually narrowing. New databases are emerging, some of which speak entirely new languages. That’s not to say that SQL isn’t popular. Rather, SQL is used more now than ever before. It’s just that the world of data storage is growing at an even faster pace, and experimentation and new branching are booming in the aftermath.

Here are eight new approaches to importing data. Some innovations are limited to the outward appearance. Some developers have updated the SQL syntax to make it a bit cleaner and easier to read to alleviate the disparity in switching tasks between writing code for the browser and fetching data. The authors of these tools emphasize that the infrastructure is virtually identical to SQL. It’s still easy to learn, so don’t worry.

Some tools require a completely different mindset. A database that stores bits as a graph or time series presents a new paradigm in how programmers specify what they are looking for.

Not all of these options are better than SQL, depending on what the user needs to do. Also, not everyone offers all the possibilities they seek. But it gives us an opportunity to think differently about the world of bites. Users only need to find a way to achieve the required task.


GraphQL has a slightly confusing name in that it is not a language designed to exploit the full potential of graph databases. Rather, it’s more of a neat shorthand for querying data stored in a nested format, similar to JSON. A query is a short description of the desired result. The backend looks at this list of fields, which may contain constraints on values, and tries to find a match. GraphQL users simply provide a list of fields, while SQL specifies “how” the database performs the request. That is why it is sometimes referred to as “query by example”.

Source: ITWorld Korea by www.itworld.co.kr.

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