A NoSQL originally referring to non SQL or nonrelational is a database that provides a mechanism for storage and retrieval of data. NoSQL databases are used in real-time web applications and big data and their use is increasing over time. NoSQL systems are also sometimes called Not only SQL to emphasize the fact that they may support SQL-like query languages. In this article, we will see about Specialty Databases and their applications of it in DBMS and sub-topics related to them.
Specialty Databases:
A collection of focused information on one or more specific fields of study is referred to as Specialty Databases. The information is stored in such a way that the user can locate and retrieve it quickly and easily.
Why Use Specialty Databases :
- Guaranteed Authoritative information: When someone searches a database they find an article that will be accurate and reliable too.
- Provide Full-text access: Text links will be available to anyone within the search results.
There are various types of Specialty Databases:
- RDBMS: RDBMS is a Relational Database Management System based on the Relational model of data. It follows a table structure, it is simple to use and easy to understand. It supports Structured Query Language (SQL).RDMS is used for traditional applications tasks such as data administration and data processing. MS SQL Server, MySQL, SQLite, MariaDB are examples of RDBMS.
- OODBMS: It adds DBMS functionalities to a programming language.When it comes to integration with host language – Flawless integration with C++/Small talk. Query language – Query processing is relatively disorganized.
- ORDBMS: ORDBMS is an Object-Oriented Relational Database Management System based on the Relational as well as Object-Oriented database model. It adds new data types to RDBMS. When it comes to integration with host language – Integration happens only through embedded SQL in a host language. Query language – SQL build standards are available.
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Object-Based Data Models: As the name suggests Object-Based Data Model is a model which is built on object-oriented programming which relates the methods that are nothing but procedures with objects that can benefit from class hierarchies. Objects are the levels of abstraction that include properties and actions. This type of data model is one that tries to focus on how to express data. The data here is divided into different units in which each unit has some defining properties. The object-oriented data model also supports a rich type system, structured and collection types. Examples of Object-Based Data Models:
- ER (Entity Relationship) Data Model
- Semantic Data Model
- Functional Data Model
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Semi-Structured Data Models: These data models were planned as an evolution of the relational data model. It is a database model in which there is no partition between the data and the schema. It allows the representation of data with a workable structure. In this data, model items can have different numbers of attributes but one item may contain items with different structures. It is a data model where the data values and the schema components synchronize properly. There are some characteristics of Semi-structured Data Models:
- One can change the schema easily.
- It gives a workable format to exchange the data between different types of databases.
- Data transfer format may be transferable.
Some Most Important Specialty Databases are as follows:
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PubMed: It has over 29 million references. It does include its sources from MEDLINE (the National Library of Medicine’s journal citation database), PubMed Central (PMC – a free archive of biomedical and life sciences articles), and many more. As the sources indicate these types of databases is ideal for :
- School of Medicine
- School of Health Professions
- Graduate School of Biomedical Sciences
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Embase: It has over 29 million records, it includes its sources from Emtree, international biomedical literature, etc. As the sources indicate these types of databases is ideal for:
- Graduate School of Biomedical Sciences
- School of Pharmacy
- School of Medicine
- Scopus: It has 49 million records, including sources from Life science, Physical/Health sciences, Social sciences.
- CINAHL: it stands for Cumulative Index to Nursing and Allied Health Literature and is pronounced as “sin-all”. Includes source from Nursing, etc.
Applications of Specialty Databases :
- It compares RDBMS, OODBMS, and ORDBMS.
- ORDBMS is a relational DBMS that has its own certain extensions.