Final answer:
Partitioning is the capability to split a table into separate sections in a database.
Step-by-step explanation:
The capability to split a table into separate sections, often called partitioning, is possible with most relational database products. Partitioning allows for improved performance, manageability, and scalability in large databases.
For example, imagine a database that stores customer information. By partitioning the table based on the customer's location, queries for customers in a specific region can be executed faster because the database can search only the relevant partition.
In conclusion, partitioning is a technique used in relational databases to divide a large table into smaller sections, resulting in better performance, organization, and scalability.
The capability to split a table into separate sections in relational database products is called partitioning. Partitioning improves the manageability, performance, and availability of a wide variety of applications by distributing a large database into more manageable pieces. While splitting might seem like an appropriate term, it is not the recognized term in this context. Similarly, combining refers to the process of merging things together, which is the opposite of partitioning, and normalizing is the process of structuring a database to reduce redundancy and improve data integrity.