1. Performance issues: Cursors can be inefficient and slow down database operations, especially when dealing with a large number of records. This is because each row accessed by the cursor requires a separate round-trip to the database, leading to increased network traffic and processing time.

To fix this issue, consider alternative methods such as set-based operations or using temporary tables to reduce the number of round-trips to the database. Additionally, optimizing the query used by the cursor and limiting the number of rows fetched at a time can improve performance.

2. Resource consumption: Cursors can consume a significant amount of memory and other system resources, especially if not properly managed or closed after use. Leaving cursors open can lead to memory leaks and degrade the overall performance of the database.

To address this issue, always close the cursor after completing the necessary operations. Make sure to release any resources associated with the cursor, such as database connections or locks, to free up memory and prevent resource exhaustion.

3. Locking and blocking: Cursors can hold locks on rows or tables while they are being processed, potentially causing blocking issues for other users trying to access the same data. This can lead to concurrency problems and impact the overall database performance.

To mitigate locking and blocking issues, consider using shorter transactions or optimizing the cursor operations to minimize the time locks are held. Use appropriate isolation levels and locking hints to control the behavior of the cursor and prevent conflicts with other transactions.

4. Cursor positioning errors: Cursors rely on the current position to navigate through the data set, and errors in positioning can lead to unexpected results or data corruption. Improper handling of cursor movement or incorrect use of fetch commands can result in data inconsistency or loss.

To avoid cursor positioning errors, always double-check the logic used to move the cursor and retrieve records. Ensure that the cursor is properly initialized and positioned before fetching data, and handle exceptions or edge cases that may affect the cursor's behavior.

5. Scalability limitations: Cursors may not scale well with large datasets or high concurrency levels, as they are designed to process data row by row sequentially. This can limit the performance and scalability of applications that heavily rely on cursors for data manipulation.

To overcome scalability limitations, consider using alternative approaches such as batch processing, parallel execution, or asynchronous programming techniques. Use cursor sparingly for small, targeted operations and avoid using them for bulk data processing or intensive data manipulation tasks.

Did you know that the concept of cursors was first introduced in the early 1970s by Edgar F. Codd, the inventor of the relational database model? Cursors revolutionized the way data could be accessed and manipulated within databases, providing a more efficient and flexible method for interacting with data. This innovation played a crucial role in the development of modern database management systems and continues to be an essential feature in database programming today.