Differences between Various DBMSs The distinction between single-user DBMSs and

Question

Differences between Various DBMSs

The distinction between single-user DBMSs and multiuser DBMSs is clear from reading the names, but there are other classifications of databases. Relational databases are the most widely used model at this time.

Using the South University Online Library or the Internet, research various types of DBMSs.

Based on your research and understanding, create a 2- to 3-page Microsoft Word document that includes answers to the following:

What are the different database models? How do these models compare with the relational model?

Do the various database models store and retrieve data differently? Explain?

What is SQL and for what purpose is it used in databases?

What is referential integrity and why is it important?

What is database concurrency and what does it prevent?

A database is self-describing. By what other name is this attribute known as?

What are the functions of a DBMS? List them and provide a brief but meaningful description of each.

What separates a personal DBMS from an enterprise-level DBMS?

Database design is important and full of challenges. Many databases are poorly designed. What are the characteristics of a poor database design?

What are the three types of database design?

In what year was the relational model developed and who developed it?

What other DBMS constructs came after relational databases?

Support your answers with examples.

Cite any sources in APA format.

Explanation / Answer

What are the different database models? How do these models compare with the relational model?

Answer:

Database model:

A database model shows the logical structure of a database, including the relationships and constraints that determine how data can be stored and accessed. Individual database models are designed based on the rules and concepts of whichever broader data model the designers adopt. Most data models can be represented by an accompanying database diagram.

There are many kinds of data models. Some of the most common ones include:

Relational model

The most common model, the relational model sorts data into tables, also known as relations, each of which consists of columns and rows. Each column lists an attribute of the entity in question, such as price, zip code, or birth date. Together, the attributes in a relation are called a domain. A particular attribute or combination of attributes is chosen as a primary key that can be referred to in other tables, when it’s called a foreign key.

Each row, also called a tuple, includes data about a specific instance of the entity in question, such as a particular employee.

The model also accounts for the types of relationships between those tables, including one-to-one, one-to-many, and many-to-many relationships

Hierarchical model

The hierarchical model organizes data into a tree-like structure, where each record has a single parent or root. Sibling records are sorted in a particular order. That order is used as the physical order for storing the database. This model is good for describing many real-world relationships.

Network model

The network model builds on the hierarchical model by allowing many-to-many relationships between linked records, implying multiple parent records. Based on mathematical set theory, the model is constructed with sets of related records. Each set consists of one owner or parent record and one or more member or child records. A record can be a member or child in multiple sets, allowing this model to convey complex relationships.

It was most popular in the 70s after it was formally defined by the Conference on Data Systems Languages (CODASYL)

Object-oriented database model

This model defines a database as a collection of objects, or reusable software elements, with associated features and methods. There are several kinds of object-oriented databases:

A multimedia database incorporates media, such as images, that could not be stored in a relational database.

A hypertext database allows any object to link to any other object. It’s useful for organizing lots of disparate data, but it’s not ideal for numerical analysis.

The object-oriented database model is the best known post-relational database model, since it incorporates tables, but isn’t limited to tables. Such models are also known as hybrid database models

Object-relational model

This hybrid database model combines the simplicity of the relational model with some of the advanced functionality of the object-oriented database model. In essence, it allows designers to incorporate objects into the familiar table structure.

Languages and call interfaces include SQL3, vendor languages, ODBC, JDBC, and proprietary call interfaces that are extensions of the languages and interfaces used by the relational model.

Entity-relationship model

This model captures the relationships between real-world entities much like the network model, but it isn’t as directly tied to the physical structure of the database. Instead, it’s often used for designing a database conceptually.

Here, the people, places, and things about which data points are stored are referred to as entities, each of which has certain attributes that together make up their domain. The cardinality, or relationships between entities, are mapped as well.

Inverted file model

A database built with the inverted file structure is designed to facilitate fast full text searches. In this model, data content is indexed as a series of keys in a lookup table, with the values pointing to the location of the associated files. This structure can provide nearly instantaneous reporting in big data and analytics, for instance.

This model has been used by the ADABAS database management system of Software AG since 1970, and it is still supported today.

Flat model

The flat model is the earliest, simplest data model. It simply lists all the data in a single table, consisting of columns and rows. In order to access or manipulate the data, the computer has to read the entire flat file into memory, which makes this model inefficient for all but the smallest data sets.

Multidimensional model

This is a variation of the relational model designed to facilitate improved analytical processing. While the relational model is optimized for online transaction processing (OLTP), this model is designed for online analytical processing (OLAP).

Each cell in a dimensional database contains data about the dimensions tracked by the database. Visually, it’s like a collection of cubes, rather than two-dimensional tables.

Semistructured model

In this model, the structural data usually contained in the database schema is embedded with the data itself. Here the distinction between data and schema is vague at best. This model is useful for describing systems, such as certain Web-based data sources, which we treat as databases but cannot constrain with a schema. It’s also useful for describing interactions between databases that don’t adhere to the same schema.

Context model

This model can incorporate elements from other database models as needed. It cobbles together elements from object-oriented, semistructured, and network models.

Associative model

This model divides all the data points based on whether they describe an entity or an association. In this model, an entity is anything that exists independently, whereas an association is something that only exists in relation to something else.

The associative model structures the data into two sets:

Other, less common database models include:

Related Questions

Navigate

• Browse (All)
• Browse D
• Subjects

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.