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A hierarchical database model is a data model in which the data is organized into a tree-like structure. The data are stored as records which is a collection of one or more fields . Each field contains a single value, and the collection of fields in a record defines its type .
The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
The basic data structure of the relational model is the table, where information about a particular entity (say, an employee) is represented in rows (also called tuples) and columns. Thus, the "relation" in "relational database" refers to the various tables in the database; a relation is a set of tuples. The columns enumerate the various ...
The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions. "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. The principle ...
Set up the table relationships – Look at each table and decide how the data in one table is related to the data in other tables. Add fields to tables or create new tables to clarify the relationships, as necessary. Refine the design – Analyze the design for errors. Create tables and add a few records of sample data.
A table in a SQL database schema corresponds to a predicate variable; the contents of a table to a relation; key constraints, other constraints, and SQL queries correspond to predicates. However, SQL databases deviate from the relational model in many details , and Codd fiercely argued against deviations that compromise the original principles.
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The nested set model is a technique for representing nested set collections (also known as trees or hierarchies) in relational databases.. It is based on Nested Intervals, that "are immune to hierarchy reorganization problem, and allow answering ancestor path hierarchical queries algorithmically — without accessing the stored hierarchy relation".