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Physical database schema: The physical database schema represents the physical arrangement of data and how it's stored in blocks of storage such as files, indices, key-value pairs. Logical database schema: Logical database schema describes the logical representation of data and conveys logical constraints.

In short, the schema is the blueprint of the database, while the instance is the actual data that is in the database. The schema is the database's design, and the instance is the data it contains. When you change the schema, you change the structure of the database.

There are two main kinds of database schema: A logical database schema conveys the logical constraints that apply to the stored data. It may define integrity constraints, views, and tables. A physical database schema lays out how data is stored physically on a storage system in terms of files and indices.

The two most common database schema designs are star and snowflake schemas. And, as their names suggest, their designs often look like visual representations of a star and a snowflake. A star schema is a simple schema design in which a single fact table is connected to one or more dimension tables.

For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects. For example, in the two schemas DB1. Student (Name, SSN, Level, Major, Marks) and DB2.

Definition: Schema integration is used to merge two or more database schemas into a single schema that can store data from both the original databases. For large databases with many expected users and applications, the integration approach of designing individual schema and then merging them can be used.