SQL Quiz — 7 Free Questions

Question 1

What is the purpose of a database VIEW?

Question 2

What is the purpose of using a database "cursor" in SQL, particularly within a stored procedure?

Question 3

What is the primary purpose of a database index?

Question 4

What is the effect of adding the SQL keyword NOT before a WHERE condition, such as NOT IN?

Question 5

What does the phrase "query optimizer" refer to within a relational database engine?

Question 6

What does CTE stand for in SQL, as introduced by the WITH clause?

Question 7

What SQL statement is used to add new rows of data into a table?

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About SQL

SQL is older than almost every other topic on this site. It traces directly back to a 1970 paper by IBM researcher Edgar Codd describing the relational model, the idea of organizing data into simple tables of rows and columns rather than the more rigid, hierarchical formats databases had used before. IBM researchers built a query language around that model shortly after, originally calling it SEQUEL, before trademark issues forced a rename to the SQL we know today.

The language got its first formal standard through ANSI in 1986, which is remarkable considering how many entirely different eras of computing SQL has now lived through since. More than fifty years after Codd's original paper, SQL remains the primary language the world uses to actually ask databases questions.

Part of what's kept it relevant is that its core idea holds up remarkably well even today: you describe what data you want, not how to go and fetch it, and the database engine figures out the fastest way to retrieve it. That declarative approach turned out to be genuinely timeless, even as the hardware and scale it runs on changed almost beyond recognition.

SQL did face a serious challenge in the 2000s and 2010s from the so-called NoSQL movement, a wave of newer databases built to handle massive scale and less structured data more easily than traditional relational databases could. For a while, some predicted SQL's decline. Instead, many of those same NoSQL systems eventually added SQL-like query layers of their own, because developers kept wanting that same familiar, declarative way of asking questions even on entirely different kinds of databases.

Not every database speaks identical SQL, either. Microsoft SQL Server uses a dialect called T-SQL, Oracle uses PL/SQL, and MySQL and PostgreSQL each have their own extensions and quirks layered on top of the same shared core language, which is one reason developers moving between database systems often need to relearn small but important details.

Nearly every backend developer, data analyst, and even plenty of product managers end up needing to read or write SQL at some point in their career, which makes it one of the most broadly useful technical skills to genuinely understand well, rather than just recognize by name.

A newer category called NewSQL has emerged more recently too, databases that try to offer the familiar guarantees and query language of traditional SQL systems while still scaling out horizontally across many machines the way NoSQL databases do, essentially trying to get the best of both worlds rather than picking one approach or the other.

SQL's staying power also shows up in how often it gets reinvented as an interface layer on top of completely different underlying technology. Modern big-data tools like Spark SQL let engineers query enormous distributed datasets using the same familiar SQL syntax they already know, which says a lot about how deeply that original 1970s query language became wired into how people actually think about working with data.

SQL's influence even shows up in casual technical interviews, where writing a correct join across multiple tables, understanding the difference between an inner and outer join, or explaining what an index actually does to speed up a query remain some of the most commonly asked questions for anyone applying to a role that touches data in any way, regardless of which specific database technology the company happens to use.