What are Functions of DBMS?

Introduction

Database Management Systems (DBMS) are indispensable in today’s data-driven world. They serve as the backbone of information management by enabling efficient storage, retrieval, manipulation, and organization of vast amounts of data. Beyond data storage, DBMS performs crucial functions such as data definition, manipulation, administration, and security.

This article dives into these functions, shedding light on their significance and real-world applications. We’ll also discuss the evolving landscape of DBMS. Understanding the functions of DBMS empowers individuals and organizations to make informed decisions and leverage the full potential of their data resources. Let’s embark on this enlightening journey of DBMS functions in the digital era.

What is DBMS?

DBMS, or a Database Management System, is fundamentally an automated data-storing system. It is a structured framework that allows you to keep, manage, and retrieve data efficiently. 

Consider a library where books are to be organized to make them more accessible to the members. You’d see a few things— books, shelves, catalogs, indexes, an authorization card, and, lastly, a librarian. Now take the librarian to be a DBMS, overseeing all operations on the components mentioned above. Books represent data; shelves could hence be data tables, catalogs would be the information document, and so on. Have you got the point? Let’s now see how this system works in more detail.

Functions of DBMS

Primarily, a DBMS manages data. But the functionality continues. There are a few more purposes for utilizing database management systems.

Security Management

Keeping massive volumes of data without a security framework makes it very prone to get compromised. Especially if you lack the technical know-how of securing or retrieving it in case of a mishap, this is where a DBMS can help you. By default, numerous security features are vested in these systems, making it easier for organizations to manage multi-user databases.

Backup and Recovery Management

In a situation where you might lose your data, certain functions of DBMS, like this one, ensure that you can get it back. Database management systems are designed for damage control—they can recover your data even if the system fails for some reason.

Data Transformation and Presentation

One of the operations you can do with a DBMS is data transformation. By this, we mean that despite how the system stores your data in separate tables, you’ll get the result in a raw format without specifying. For instance, a DMBS might store DOBs in separate tables for dates, months, and years. But when you retrieve an entry, you will get a date of 7 September 2023.

There are many more functions you can do in a DBMS, like data definition, data manipulation, retrieval and reporting, concurrency, multi-user access control, data integrity management, communication and application programming interfaces, and a lot more. Let’s delve deeper into some of the most widely used functions of DBMS.

Data Definition Function

As the name suggests, this DBMS function defines and manages the database structure. It involves creating, modifying, and removing objects like tables, indexes, etc. 

Creating and Modifying Database Schema

Creating and modifying the database schema is essential to the data definition function.  Simply put, a schema defines how a database organizes data using logical constraints, tables, etc.

• Defining Data Types, Constraints, and Relationships: Further, creating a schema also includes specifying the overall structure, including the relationships between data points, their columns (or rows), and data types. This is where you tell the system how you want it to store the data. For instance, when storing student data, you can specify the columns as “Roll Numbers,” “Attendance,” “Name,” and anything else that you wish to record. 
• Modifying Schema: Over time, the requirements of the database may change, necessitating modifications to the existing schema. This can be done using the data definition function of a DBMS, where you can alter the number of rows/columns, add more data types or constraints, and do a lot more.

Continuing the above example, the modification could involve adding more rows for newer admissions or deleting the column having names to keep the records anonymous.

Data Manipulation Function

These functions of DBMS enable you to manipulate data as per your requirements: 

Inserting, Updating, and Deleting Data

These data manipulation functions make the experience much more interactive for the users.

• Insertion involves adding new data records or rows into the database tables. For example, you can add a column “Total leaves taken” in the student record database described above. 
• While updating, this function allows you to modify or update existing records. For instance, in the above example, you could update the “Attendance” column daily.
• Deletion, as the name says, allows you to delete specific records or even entire datasets. In the example above, deletion could imply removing a student’s entry once they drop out of the class/school.

Querying and Retrieving Data

Etymologically, querying means posing questions. DBMS terminology translates to sending requests to the database to get specific information. Users can formulate queries using Structured Query Language (SQL) or other query languages supported by the DBMS. For instance, following the student database example, you could pass a query to get all students with 100% attendance.

On the other hand, retrieving data involves picking a particular record or certain values based on the query you executed. Simply put, after executing the query, the data manipulation function allows you to retrieve data and make it available in an understandable format. In the example above, you could retrieve the records of the last student administered in the database.

Data Retrieval and Reporting Function

Such functions of DBMS allow you to extract data and then use it to generate reports for analysis and, ultimately, decision-making. 

Database systems enable you to generate reports using predefined templates or even custom layouts to better visualize the data. You can define report templates with specific sections, headers, footers, and formatting options here. The DBMS can fill in the templates with the retrieved data, arrange it, and even perform aggregations.

Data Security and Integrity Function

One of the most respected functions of DBMS is data security and integrity. While data security ensures that your data is kept away from unauthorized users, data integrity warrants that the data is complete and consistent.  Let’s learn more in detail.

Implementing Access Control Mechanisms

Tools, safeguards, and measures are put in place in a DBMS to ensure that data remains confidential and accessible only to authorized parties. This includes protecting the data, associated applications, the server, underlying hardware, and the network infrastructure. 

Access control as a part of the functions of DBMS is done via two primary mechanisms: authentication and authorization. The former confirms a user’s identity, and the latter oversees the level of access when the authenticated user accesses the database.

While it is vital to your data for obvious reasons, it is also an unavoidable compliance factor for DBMS service providers, as they can face heavy fines and penalties for non-compliance. Regulatory authorities like HIPAA and Europe’s GDPR are some governing bodies that keep data service providers in line.

Enforcing Data Integrity Constraints

A DBMS constraints/restricts the values that users can insert or remove from the data. For example, in the student record database, if you’ve administered that only students with a roll number can be recorded in the database, then any other authenticated user cannot insert a student’s records whose roll number is missing. This ensures that data is consistent within the database.

Data Backup and Recovery Function

All computerized systems can fail unexpectedly for many reasons, like user error or some hardware failure. What people worry about the most in such situations is data loss. But with a robust DBMS, you can be free of the agony.

Creating Backup Copies of the Database

You can back up your data in the database in three main ways. These are Full Backup, Transaction Log, and Differential Backup. 

• Full Backup: It creates a complete database copy, making it the most time-consuming method.
• Transaction Log: Here, only transaction logs are copied and stored as backup. However, the previous logs get deleted once a new backup is generated to ensure minimal memory usage.
• Differential Backup: Similar to a full backup, the differential backup saves only the data that has been altered since the previous full backup.

Restoring the Database in the Case of Failures

Prominent functions of database management systems offer two primary techniques to restore data in case of database failure.

• Rollback or Undo Recovery: The technique follows from backing out or reversing the effects of an unsuccessful transaction due to system failure. Here, the DBMS reverses the changes using log records. The process goes on till data is restored.
• Commit or Redo Recovery: This technique reapplies the alterations in a successful transaction in the database. The reapplication is done using the log records to replicate later the changes done at the time of system failure.

Data Concurrency Control Function

Concurrency control functions are implemented to ensure that two simultaneously running processes are executed without any hassle/conflict.

Managing Concurrent Access to the Database

To prevent concurrency issues, you can manage access to the database. This can be done via

• Lock Concurrency Control: You can use the metadata to determine which data points will be locked. This helps with concurrency control as the mechanisms often lock segments of data to avoid conflicts.
• Granularity Locking: Different lock granularities, such as row-level, page-level, or table-level locks, can be used based on access patterns and concurrency requirements.

Handling Simultaneous Transactions

To prevent any concurrency issues while storing data, use transactions. Transactions are units of one or more SQL commands the server executes. The ones that follow the ACID (Atomicity, Consistency, Isolation, and Durability) theory ensure no concurrency conflicts while you store information.

Data Dictionary Function

A data dictionary, also known as a metadata repository or data catalog, is a component that stores and manages metadata about the database objects and structures.

Maintaining Metadata About the Database

The data dictionary in functions of DBMS allows you to include infrastructure information like table names, column names, data types, lengths, indexes, and several other attributes. You can take it as a reference document that defines the database schema.

Storing Information About Tables, Columns, and Relationships

Using this function, you can store all necessary information about the tables, columns, and relationships in a central repository—the data dictionary. It stores table names, length, statistics, column names, constraints, foreign key relationships, and more.

Data Transformation and Integration Function

Data transformation becomes way more important when you have massive volumes of raw data. Moreover, integrating it once you have a consistent format is another important function. Both of these DBMS functions enable data to be transformed, consolidated, and integrated into a format suitable for analysis, reporting, or other business purposes.

Converting and Integrating Data from Different Sources

There are several techniques that you can use to convert and integrate data from multiple sources. This may include the following:

• Data Extraction: It involves connecting to databases, accessing APIs, and reading files in different formats (e.g., CSV, XML, JSON).
• Data Mapping: It involves identifying the corresponding attributes, fields, or columns in the source and target systems.
• Data Transformation: It involves converting the extracted data to match the desired format, structure, or schema of the target database.
• Data Integration and Consolidation: It involves performing data joins, merging datasets based on common keys or attributes, and resolving any conflicts or inconsistencies between the integrated data sources.

Ensuring Data Consistency and Coherence

It is primitive to ensure the data you integrate from multiple sources is consistent and coherent. By consistency, we imply that data should belong to the same type. On the other hand, coherency would mean logical uniformity across data from different sources, i.e., all data points make sense. DBMS does this by data validation, transaction management, concurrency control, data normalization, and using referential integrity.

Data Privacy and Compliance Function

Data privacy and compliance operations are essential to ensure that organizations handle and secure sensitive data in accordance with applicable laws, regulations, and industry standards. 

Implementing Measures to Protect Sensitive Data

There are several measures that database management systems undertake to protect sensitive data. This includes

• Data classification and protection,
• Consent management,
• Data break management,
• Employee training and awareness.

Complying with Data Privacy Regulations 

DBMS technologies are always updated on applicable privacy laws and regulations and ensure organizational compliance. This includes conducting privacy impact assessments, maintaining records of data processing activities, fulfilling individuals’ rights (e.g., access, rectification, erasure), and appointing a Data Protection Officer (DPO) if required by law.

Data Performance Optimization Function

As database systems manage multiple databases for hundreds of users simultaneously, performance optimization is the most significant factor. These DBMS functions involve implementing strategies to manage data storage, access, retrieval, and processing.

Indexing and Optimizing Query Execution

Indexing is essential for improving the effectiveness of the data retrieval process. Database systems can quickly discover and obtain the required data by generating appropriate indexes on frequently requested columns, eliminating the need for total table searches.

Whereas query optimization includes techniques such as rewriting queries, restructuring table schemas, using appropriate join algorithms, and leveraging query hints.

Improving Database Performance and Efficiency

One way that DBMS technologies improve efficiency is by caching. Caching significantly reduces the response time of read-intensive operations, especially for data that is relatively static or expensive to fetch from disk. Moreover, data partitioning can improve performance by enabling parallel processing, reducing I/O operations, and enhancing data availability.

Data Migration and Conversion Function

Seamless data migration is one of the most valid reasons for opting for a database management system as it entirely deprecates the necessity of you having the technical know-how of migration.

Moving Data from One Database to Another

When it comes to moving data from one database to another in a database management system (DBMS), there are several approaches you can take depending on the requirements. Some of the standard methods are

• Built-in export/import utilities for various supported formats, like CSV, XML, etc.
• ETL (extract, transform, and load),
• Linked servers or database links,
• Custom programming.

Converting Data Formats During Migration

In case your data is not in a format that can be migrated, DBMS functionality allows you to convert it using functions like CAST or CONVERT. These can convert data types in SQL queries.

Moreover, If the source and target databases use different character encodings (e.g., UTF-8, ASCII, ISO-8859-1), DBMS helps with character encoding and transliteration to convert special characters.

Data Archiving and Purging Function

Database management systems also facilitate archiving (storing) and purging (freeing up space/deleting) data. 

Archiving Old or Infrequently Accessed Data

To save up memory, it is suggested to archive the data that is not in frequent usage and make that space available for newer data. In a DBMS, this can be done by

• Determining the criteria for selecting data that can be archived, such as data age, last access date, etc. 
• Designating a separate storage location.
• Moving the selected data by using export/import utilities or mechanisms like INSERT INTO.
• Running SQL queries.

Purging Obsolete or Redundant Data

Often, there will be no more relevant data, and it holds no value to be stored. In such a scenario, database management systems also allow you to purge it, i.e., free up the space it takes. DBMS allows you to use statements like DELETE and TRUNCATE or provides built-in program pipelines that purge data after a predetermined period.

Data Replication and Synchronization Function

Functions of DBMS also include data replication and synchronization. They are used to maintain consistent and up-to-date copies of data across multiple databases or database instances.

Replicating Data Across Multiple Databases or Servers

DBMS offers several replication options, like

• Master-slave replication: a single database acts as the master and propagates changes (inserts, updates, deletes) to one or more slave databases.
• Multi-master replication: multiple databases act as masters, and changes made on any master database are propagated to other master databases.
• Peer-to-peer replication: all databases are peers and can act as both master and slave.
• Statement-Based Replication: Here, replication is performed by replicating the SQL statements.

Ensuring Data Consistency Across Replicas

The functions of DBMS do not end at data replication. It also ensures the replicated data is consistent across replicas. This can be done via

• Synchronous Replication: In synchronous replication, alterations made on the master database are applied synchronously to all replica databases before confirming the transaction’s completion.
• Asynchronous Replication: Asynchronous replication allows for some replication delay by having changes made to the master database propagate to the replica databases simultaneously.

Applications of DBMS

Database management systems are used for several real-world applications. Some of them are

• The Indian railway and airline systems heavily rely on DBMS technologies to store travel data. This is done for several purposes—ticketing, passenger information management, flight/rail scheduling and planning, inventory management, and a lot more.
• Social media websites like Facebook, Instagram, and Snapchat also utilize database management systems. This is done for user profile management, content storage, news feed and timeline management, social graphing, advertising, targeting, and real-time data processing.
• Online shopping platforms like Amazon, Flipkart, and eBay also use databases to store customer data. DBMS technologies help them with product catalog management, customer management, order processing, customer reviews, and ratings, security, and fraud prevention.

Conclusion

In conclusion, a database management system (DBMS) is essential to an organization’s ability to manage data effectively. Its functionalities include data organization, archiving, retrieval, security, upkeep, and performance improvement. Alongside aiding data transformation, integration, migration, and replication, the functions of DBMS also guarantee consistency, coherence, privacy, and compliance.

Analytics Vidhya (AV) can be a valuable resource for learning more about DBMS and its features. As a well-known online platform, Analytics Vidhya provides a variety of courses, tutorials, articles, and community forums on many data-related subjects, including DBMS. Not just these, the platform also prepares you for a tech-driven future in modern-day technologies like AI and ML using one-on-one mentorship programs like Blackbelt+. So without wasting your time, head over to the website and explore.

Frequently Asked Questions