Database Management System: DBMS Definition and Examples
May 2, 2020
With each passing year, organizations have to process more and more data. Without verifying and organizing this information, however, it is of little use. Incomplete databases and poorly updated documents can increase the risk of operational mistakes. When databases are improperly managed, it can completely shutter business operations.
Such risks can be mitigated with the help of database management systems (DBMSs), an essential part of data science. These are software systems that can access, store, retrieve and update data on databases. This guide will help you understand why these systems are essential and how they can streamline data management.
Functions of Database Management Systems
What are the features and capabilities of a DBMS? These systems are vital for reducing data redundancy and validating data integrity. Among the many processes this entails, DBMSs can help organizations do the following:
Serve as an interface between databases and users.
Store, retrieve and update information.
Organize data into useful formats, including tables, schema and reports.
Publish information online in an accessible fashion.
Allow users from around the world to collaborate on data management.
Set role restrictions so that only authorized individuals can access pertinent data.
Provide security for saved data, including data backup and recovery.
There are many stakeholders involved in DBMSs. This includes the individuals who develop them, the managers who use them and set role restrictions, the employees who interface with them, and the shareholders and consumers who access organizational data for informational purposes. A DBMS must be designed with each of these users in mind in order to properly serve every stakeholder.
If you’ve worked with data as a student or in a professional capacity, you may have already had some hands-on experience with a DBMS. Indeed, there are many systems that developers use today. Some popular databases include:
Altibase: This enterprise-grade, open-source software allows access to memory-resident and disk-resident tables through a single interface. This makes it a versatile option for developers working with both in-memory and on-disk databases.
FileMaker: FileMaker is a relational database that integrates a database engine with a graphical user interface. Users can modify the database by simply clicking and dragging elements to where they need to go. It is cross-platform and can connect to many SQL databases without using SQL.
IBM Db2: An AI-powered DBMS that uses machine learning to optimize queries. It supports many data types and coding languages, including NoSQL, pureXML, Java and Python. It is easy to install and use.
Microsoft Access: This system also combines a relational database engine with a graphical user interface to provide accessible database management capabilities. Access was designed to enable users to access and update data from any source, making it a vital tool for many organizations.
MySQL: This is a free, open-source relational DBMS that has cross-platform support and can run on many cloud computing programs. “Relational” refers to the fact that it demonstrates how different data points relate to one another. When used with MySQL Workbench, it is an accessible option for database management.
MongoDB: This is an example of a NoSQL database. Similar to MySQL, these are generally free and open-source DBMSs. Unlike MySQL, they focus on non-relational database management. These are commonly used for big data and real-time applications on the web.
PostgreSQL: Also known as Postgres, this is also a free, open-source relational DBMS. Notably, it is the default database for macOS Server, though it can be used across Linux and Windows OSs.
These are only a few examples of the many free and commercial DBMSs available. Each has different strengths and weaknesses, and many are well-suited for specific use cases. Learn more about these systems below.
Types of Databases
There are many kinds of database models in DBMSs. Each is designed for accessing different types of information, has different use cases, and is sometimes best used in specific industries. Review the different types of systems below to learn more.
A type of database in NoSQL, document databases are fairly popular methods of storing and retrieving documents. They are starkly different from relational databases in that, instead of storing data in separate tables, all information for an object can be stored in a single instance. This allows for a greater variety of data to be stored and makes it easier to store or retrieve data. However, they generally lack information about the relationships between data points. Like relational databases, document databases see use in a wide range of fields.
NoSQL databases that use a graphical structure for queries are called “graph databases.” These databases store data as nodes, edges (relationships between nodes), and properties (further information about each node and relationship). These databases can provide clear and accessible representations of information, which can make them useful for data visualization.
Hierarchical databases store data with a tree-like structure of parent-child relationship nodes. One parent node can have one or multiple child nodes, but each child only has one parent. Data are stored as records and the first record is the root node. There are many uses for hierarchical databases, and they were commonly used for data management by financial institutions.
As their name suggests, network databases use a network structure to create relationships between different data points. Unlike hierarchical databases, nodes in network databases can have many relationships with other nodes. Further, while the structure in hierarchical databases is composed of parent-child relationships, network databases use occupier-member relationships. This more accurately reflects the many different relationships the nodes may have. These databases are generally used for large networks of computers, and they have many applications in a wide variety of industries.
A useful tool for C++ and Java, object-oriented databases have all the database programming abilities you’ll need while using programming languages. While these require advanced programming knowledge, they streamline the coding process by using more natural data modeling. Objects, which are used in object-oriented programming, are stored in the database. They can be used and remixed in an endless number of ways, making them great for multimedia production. However, they can be expensive and time-consuming to use.
Perhaps the most common type of database, this type of database involves tables of rows (called records or tuples) and columns (called attributes or fields) to catalog data and create relationships between entities. Tables can be linked to each other through data they both have in common. Each row has a key field, and one query can connect different tables together to create new tables. Relational databases are very accessible and see widespread use in many industries.
The Role of Database Administrators in Database Management Systems
Database administrators (DBAs) are responsible for completing a number of essential duties in regard to database management. They may be responsible for designing, installing, configuring, migrating, monitoring, securing or troubleshooting databases; the exact nature of a DBA’s work depends entirely on the needs of the organization.
DBAs must meet education requirements and have a strong skill set on database theory and design, as well as coding. They need either a bachelor’s degree or a master’s degree in data science or computer science, depending on their desired career trajectory. A wide variety of schools offer programs suited to someone seeking a career in database administration.
Some examples of skills an administrator will need include a knowledge of:
Relational database management
Storage technologies and networking
Structured query language
DBAs play a vital role in organizations. With these skills and knowledge, database administrators are responsible for installing and maintaining software, handling data, setting up employee access to data (including defining roles), coordinating analytics, and performing thorough analyses of database performance so that future improvements can be made. They are also often responsible for backing up and recovering databases in the event they are compromised.
Data now plays an integral role in organizations, and a DBA is required to put that data to work. They may work in conjunction with fellow data scientists and data engineers to create and maintain a data management plan that allows the organization to leverage data to its full potential.