Database Management Systems Models

A database management system (DBMS) is a complex of software and language tools that allow you to create databases and manage data. In other words, a DBMS is a set of programs that allows organizing, controlling, and administering databases (Meier & Kaufmann, 2019). Most sites cannot function without a database, so the DBMS is used almost everywhere. Today, relational databases are still the most popular in creating web applications and services. Relational databases are managed using SQL, a structured query language. Initially, SQL was a tool for user interaction with a database, but over time, the language has become more complex and has become more of a developer tool than an end-user.

In the relational model, both objects and their relationships are represented only by tables and nothing more. Various ratings of the most popular DBMS are headed by Oracle, MySQL, Microsoft SQL Server, PostgreSQL (Openko et al., 2019). MySQL is an open-source relational database management system; the main advantages are its speed and flexibility, which is provided by support for many different types of tables. In addition, it is a reliable free system with a simple interface and the ability to synchronize with other databases. Together, these factors make MySQL suitable for large corporations and small companies alike. PostgreSQL is most widely used for managing databases of websites and various services. As an object-relational database management system, it has several advantages over complementary products. Large companies use Oracle due to its high license cost.

Recently, non-relational databases have become widespread, which use a non-traditional approach to storing and accessing NoSQL data. There are often four types of NoSQL databases: key-value databases, document databases with a column-family structure, and graph databases. The first two types are highly aggregate-oriented because they are made up of many aggregates, each with a key or identifier used to access the data. The difference between them is that the document base sees the structure of the aggregate, while the “key-value” does not. Key-value databases most often search for aggregates by key. In the documentary, one can submit a request based on the document’s internal structure (Gupta et al., 2017). Examples include Neo4j, MongoDB, FlockDB, and Virtuoso. Since this industry is quite promising, many new products appear on it.

NoSQL databases are characterized by the following key features: the ability to scale out “simple operation” throughput across many servers and the ability to replicate and distribute data across many servers. Traditional relational databases cannot provide this flexibility. Moreover, the call level protocols and the simplicity of the interface are also distinguished by new logical models that allow dynamically working with attributes in a data record and efficiently using RAM. However, these DBMSs have a weaker concurrency model than transactions, which have the ACID properties of most relational database systems. Over the years, relational databases have been well studied, and as a result, a wealth of reference information on this subject can be found on the net. NoSQL is a relatively young technology that many developers are not yet available. Finally, the most crucial property and the difference is data retrieval reliability. Classic relational models can spend more resources on storing and retrieving information, but they provide reliable access to any record. Some of the NoSQL DBMSs allow working with big data, but eventually, some may be lost or not found by the search query.


Gupta, A., Tyagi, S., Panwar, N., Sachdeva, S., & Saxena, U. (2017). NoSQL databases: Critical analysis and comparison. In 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN) (pp. 293-299). IEEE. Web.

Meier, A., & Kaufmann, M. (2019). SQL & NoSQL databases. Springer Fachmedien Wiesbaden.

Openko, P. V., Hohoniants, S. Y., Starkova, O. V., Herasymenko, K. V., Yastrebov, M. I., & Prudchenko, A. O. (2019). Problem of Choosing a DBMS in Modern Information System. In 2019 IEEE International Conference on Advanced Trends in Information Theory (ATIT) (pp. 171-174). IEEE. Web.

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