Record-at-a-time, also known as row-at-a-time, refers to a database processing technique that retrieves or processes one record (row) at a time. In other words, the database engine fetches each row individually and processes it before moving on to the next row.
This technique is used in many database operations such as querying, sorting, filtering, and updating data. It is often used in online transaction processing (OLTP) systems where users require quick and immediate access to individual records.
The main advantage of the record-at-a-time technique is its low memory requirements and efficient use of resources. Since only one record is processed at a time, it can be quickly retrieved and processed without requiring large amounts of memory or processing power. This makes it ideal for processing large volumes of data or for real-time applications where performance and responsiveness are critical.
However, the record-at-a-time technique can also be less efficient than other processing techniques, such as set-at-a-time, when dealing with large amounts of data or complex queries. This is because each row must be processed individually, leading to increased processing time and overhead.
Aryan Kumar
28-Apr-2023Record-at-a-time, also known as row-at-a-time, refers to a database processing technique that retrieves or processes one record (row) at a time. In other words, the database engine fetches each row individually and processes it before moving on to the next row.
This technique is used in many database operations such as querying, sorting, filtering, and updating data. It is often used in online transaction processing (OLTP) systems where users require quick and immediate access to individual records.
The main advantage of the record-at-a-time technique is its low memory requirements and efficient use of resources. Since only one record is processed at a time, it can be quickly retrieved and processed without requiring large amounts of memory or processing power. This makes it ideal for processing large volumes of data or for real-time applications where performance and responsiveness are critical.
However, the record-at-a-time technique can also be less efficient than other processing techniques, such as set-at-a-time, when dealing with large amounts of data or complex queries. This is because each row must be processed individually, leading to increased processing time and overhead.
Sumit Kesarwani
22-Sep-2014The Low level or Procedural DML can specify and retrieve each record from a set of records. This retrieve of a record is said to be Record-at-a-time.