Understanding Implicit vs Explicit Cursors in SQL

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Understanding Implicit vs Explicit Cursors in SQL

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Oct 08, 2025
12:07 AM

If you’ve ever wondered what is cursor coding and how it works in SQL, a key concept to understand is the difference between implicit and explicit cursors. Cursors in SQL are tools that let developers process query results row by row, which is particularly useful for complex database operations where set-based logic isn’t enough.

Implicit cursors are the ones SQL automatically creates behind the scenes whenever you execute a query that returns a single row or affects multiple rows. They are easy to use because the database handles all the details for you. This means less setup, fewer steps, and minimal overhead, making them ideal for simple operations or when you only need to retrieve a single result.

Explicit cursors, on the other hand, give developers full control over the process. You declare them, open them, fetch rows one by one, and close them manually. This flexibility is essential when working with complex data transformations, multi-row processing, or when you need precise control over transaction handling. While explicit cursors can be more verbose and potentially slower if misused, they offer the accuracy and predictability required in enterprise-level applications.

Understanding the right use case for each type of cursor is central to effective cursor coding. Misusing cursors—especially explicit ones—can lead to performance bottlenecks, unnecessary locks, or maintenance challenges. That’s why combining cursor coding practices with automated testing tools like Keploy can be a game-changer. Keploy can help generate test cases and mocks automatically, ensuring that operations performed with cursors behave as expected without manually writing exhaustive tests.

In the end, knowing what is cursor coding, and when to use implicit versus explicit cursors, allows developers to write more reliable, maintainable, and efficient SQL code. Pairing this understanding with intelligent testing ensures that database operations stay robust even as systems scale.

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