Top 15 DBMS Interview Questions You Need to Know for 2023 – IQCode

Most Commonly Asked DBMS Interview Questions

If you want to consolidate your knowledge of DBMS and ace your interview, here are some of the most commonly asked DBMS interview questions:

Basic DBMS Interview Questions

1. Can you explain what DBMS is and its utility? Please provide examples of RDBMS.

DBMS stands for Database Management System. It is a software that is used to manage and store data efficiently and securely. It allows multiple users to access the data at the same time while maintaining data integrity and security. With the help of DBMS, users can easily add, delete or modify data. 

RDBMS stands for Relational Database Management System. It stores data in tabular form and each table has a unique identifier (primary key) that is used to establish relationships between tables. Some popular examples of RDBMS are MySQL, Oracle, and Microsoft SQL Server.

What is a Database?

A database is a collection of structured data that is organized in a way to allow efficient storage, retrieval, and manipulation of information. It is designed to manage and store large amounts of data while providing fast, easy access to that data. Databases are used in a variety of applications, including websites, business management systems, and scientific research. They can be managed using specialized software known as database management systems (DBMS).

Issues with Traditional File-Based Systems that Make DBMS a Better Choice

Traditional file-based systems have several issues that make a DBMS a better choice:

  1. Data Redundancy: In file-based systems, data is often duplicated, leading to redundancy and inconsistency. For example, if a company has multiple departments, each department may have its own file containing employee information. This leads to duplication of data, as each file will have data about the same employee. DBMS eliminates redundancy and ensures that data is consistent across the system.
  2. Data Inconsistency: As mentioned earlier, redundant data can lead to inconsistency. For example, if an employee's salary is updated in one department's file, it may not be updated in another department's file. This can lead to errors and incorrect information. DBMS ensures that data is consistent across the system and any updates or changes are reflected in all relevant locations.
  3. Data Isolation: In file-based systems, data is often isolated in different departments or applications, making it difficult to access and manage. DBMS provides a centralized location for data storage and management, making it easier to access and manipulate data.
  4. Data Security: File-based systems are often less secure than DBMS, as they are prone to data loss or corruption. DBMS provides features such as backup and recovery, access control, and data encryption to ensure data security.
  5. Data Access: In file-based systems, data access is often limited to specific users or applications. DBMS provides more advanced access control features, allowing for more granular control over who can access and modify data.
Overall, a DBMS provides a more reliable, secure, and efficient way to manage data compared to traditional file-based systems.

Advantages of a DBMS

A database management system (DBMS)

offers several advantages for organizations that handle large amounts of data:

1. Improved Data Sharing:

A DBMS allows multiple users to access and modify data concurrently. Users can work on the same data without conflicts or inconsistencies, improving collaboration and workflow.

2. Data Security and Consistency:

A DBMS provides mechanisms to protect data from unauthorized access or modification. It ensures that data is consistent by enforcing data integrity constraints, such as primary key and foreign key constraints.

3. Improved Data Access and Availability:

A DBMS provides tools for searching, filtering, and retrieving data quickly and efficiently. It supports concurrent access to data, ensuring that users can access data when they need it.

4. Reduced Data Redundancy:

A DBMS eliminates data redundancy by storing data in a centralized location. It ensures that data is consistent and up-to-date, and reduces the risk of data inconsistencies and errors.

5. Improved Data Maintenance:

A DBMS provides tools for backup and recovery, data analysis, and performance tuning. These tools help organizations to ensure the integrity and availability of their data over time.

Explanation of Different Languages Used in DBMS

DBMS (Database Management System) uses various programming languages for different purposes as follows:

1. Data Definition Language (DDL): DDL is used to define, modify, and delete the database structure or schema. Examples of DDL include SQL, XML, and JSON.

2. Data Manipulation Language (DML): DML is used to manipulate data in the database. Examples of DML include SQL, PERL, and Python.

3. Query Languages: Query languages are used to retrieve data from the database. Examples of query languages are SQL, XQuery, and SPARQL.

4. Data Control Language (DCL): DCL is used to control access to the database. Examples of DCL include SQL, Oracle, and Microsoft SQL Server.

5. Transaction Control Language (TCL): TCL is used to control transactions in the database. Examples of TCL are SQL, MySQL, and PostgreSQL.

It is essential to have a good understanding of these languages to effectively operate and manage a DBMS.

Understanding Acid Properties in DBMS

ACID (Atomicity, Consistency, Isolation, Durability) properties are essential characteristics that ensure reliable and accurate processing of database transactions in a DBMS (Database Management System).

Atomicity: It refers to the feature that each transaction in the database system is treated as a single unit of operation that must either complete in its entirety or not done at all. Atomicity ensures that if any part of the transaction fails, the entire transaction is rolled back to its previous state.

Consistency: It implies that the database's state after transaction execution will be consistent with the defined rules and constraints. The database system should ensure the data's correctness and integrity, even if the transaction execution is interrupted in the middle.

Isolation: It means that each transaction's execution is isolated from other transactions executed simultaneously. It enables each transaction to execute independently without interfering with the execution of other transactions.

Durability: It refers to the guarantee that committed transactions will persist and won't be lost permanently, even in the event of a system crash or error. The database system must make sure that updates made to the database during the transaction are stored permanently, even if there is a power outage or system failure.

By adhering to these ACID properties, DBMS ensures the integrity and reliability of data processing, ensuring that all transactions are processed securely and accurately.

Are Null Values in a Database Equivalent to Blank Spaces or Zeros?

In a database, null values and blank spaces or zeros are not the same. Null values represent missing or unknown data, while blank spaces or zeros represent intentionally inputted values. It is important to distinguish between these types of values in order to accurately analyze and manipulate data in a database.

Intermediate DBMS Interview Question:

8. Can you explain the concept of data warehousing?

Different Levels of Data Abstraction in a DBMS

In a Database Management System (DBMS), there are three levels of data abstraction:

1. Physical Level: This is the lowest level of abstraction, which deals with how data is actually stored on the storage media such as hard disk, magnetic tape, or any other storage device.

2. Logical Level: This level describes the data stored in the database and the relationships between them. It provides a description of the logical structure of the data.

3. View Level: This is the highest level of abstraction, which describes only a part of the entire database. It is the user's view of the database, which is customized according to the user's requirements.

The advantages of using multiple levels of data abstraction include:

- Data independence, where changes at one level do not affect the other levels - Security, where users can only access the data they are authorized to view - Flexibility, where users can customize their views according to their needs.

These levels of abstraction help in hiding the complexity of the data and provide an organized and easy-to-use view of the database to the users.

Understanding Entity-Relationship (E-R) Model in DBMS

An Entity-Relationship (E-R) model is a conceptual data model in database management systems that represents the relationships between entities using diagrams.

An entity refers to a real-world object or concept that has a distinguishable identity and can be uniquely identified. An entity type is a category of entities that share the same attributes. For example, "customer" can be an entity Type, and each customer would be an individual entity within that type.

An entity set is a collection of similar entities that share the same entity type. For instance, "all customers who have placed an order" would make up an entity set of customers.

E-R diagrams help to visualize the relationships between these entities and simplify the database design process. Overall, the E-R model plays a crucial role in designing and organizing data in a database.

Different types of relationships amongst tables in a DBMS

In a DBMS, there are three types of relationships between tables: one-to-one, one-to-many, and many-to-many.

1) One-to-one relationship: In this type of relationship, a record from one table is associated with only one record in another table, and vice versa. For example, a person can have only one passport, and a passport can be assigned to only one person.

2) One-to-many relationship: In this type of relationship, a record from one table is associated with multiple records in another table, but each record in the second table is associated with only one record in the first table. For example, a customer can have multiple orders, but each order can be assigned to only one customer.

3) Many-to-many relationship: In this type of relationship, multiple records from one table are associated with multiple records in another table. To create a many-to-many relationship, a junction table is required, which contains foreign keys from both tables. For example, a student can have multiple courses, and each course can have multiple students. The junction table would contain the student ID and course ID to link the two tables.

Understanding and properly implementing database relationships is essential for maintaining data integrity and preventing data inconsistencies.

Explaining the Difference Between Intension and Extension in a Database

In a database, the intension refers to the definition or the meaning of the data stored in it. It represents the attributes or properties that define the data. For instance, in a database of employees, the intension includes the job title, date of joining, department, salary, and other attributes that define an employee.

On the other hand, the extension in a database is the actual set of the data stored in a particular database instance. It includes the records or tuples present in the database. For example, the extension of the employee database includes all the details of every employee, such as their name, address, contact information, and more.

In short, intension defines what the data in the database is, while extension represents the actual data stored in a particular database instance. Knowing the difference between the two is essential for having a complete understanding of how databases function.

Explanation of the Difference between DELETE and TRUNCATE Command in DBMS

In a DBMS, DELETE and TRUNCATE are two commands that are used to remove data from a table. However, there are some significant differences between the two commands.

DELETE is a command that is used to remove specific rows or records from a table based on some conditions specified in the WHERE clause of the query. This command removes data row by row and can be rolled back, meaning that the deleted data can be restored using the rollback command.

On the other hand, TRUNCATE is a command that is used to remove all of the data from a table at once. Unlike DELETE, TRUNCATE does not require a WHERE clause and removes the data much more quickly. However, it cannot be rolled back, meaning that once the TRUNCATE command is executed, the data is lost permanently.

In summary, DELETE removes data row by row, can be rolled back, and requires a WHERE clause, while TRUNCATE removes all data at once, cannot be rolled back, and does not require a WHERE clause.

Explanation of Shared and Exclusive Locks in Database Transactions

In databases, a lock is a mechanism that controls concurrent access to data. It ensures that multiple transactions access data in a consistent and reliable manner.

A shared lock allows multiple transactions to read the same data simultaneously but prohibits modification of the data until the lock is released. On the other hand, an exclusive lock prohibits any other transaction from accessing or modifying data until the lock is released.

The major difference between a shared lock and an exclusive lock is the level of access to the data. A shared lock allows for concurrent read access while an exclusive lock restricts access from others until the transaction is finished.

In summary, while a shared lock allows multiple transactions to read a data item simultaneously, an exclusive lock restricts access to it until the transaction holding the lock is completed.

Normalization and Denormalization Explained

In the context of database design, normalization is the process of organizing a database in a way that reduces redundancy, dependency and inconsistencies. A normalized database is typically split into smaller tables that are interrelated through relationships, which makes database queries more efficient and minimizes data duplication.

On the other hand, denormalization is the opposite of normalization, where a normalized database is redesigned to include redundant data in order to speed up database queries at the expense of data duplication and greater storage requirements. Denormalization can improve application performance but at the same time, can lead to data integrity issues if not implemented correctly.

Advanced DBMS Interview Questions

In a DBMS, there are several types of normalization forms that are used to organize data in a way that minimizes redundancy and improves data integrity. Here are the different types of normalization forms:

1. First Normal Form (1NF): In this form, each column in a table is unique and there are no repeating groups or arrays of data. This ensures that each cell in a table contains a single value.

2. Second Normal Form (2NF): In this form, the table is already normalized to 1NF and each non-key column is dependent on the entire primary key. This means that a table will have a composite primary key, and all columns in the table depend on that key.

3. Third Normal Form (3NF): In this form, the table is already normalized to 2NF and no non-key column is dependent on another non-key column. This form is used to eliminate data redundancy.

4. Fourth Normal Form (4NF): In this form, no multi-valued dependencies exist for a table. It is often seen as optional or too difficult to use in practice.

5. Fifth Normal Form (5NF): In this form, the table design eliminates redundancy that can occur as a result of combining two or more one-to-many relationships.

Explaining Different Types of Keys in a Database

In a database, keys are used to establish relationships between tables and ensure data integrity. Here are the different types of keys in a database:

  • Primary key: A primary key is a unique identifier for each record in a table. It cannot be null and must be unique for each record. It is used to link tables and enforce data integrity.
  • Foreign key: A foreign key is a field in one table that refers to the primary key in another table. It is used to establish relationships between tables and ensure referential integrity.
  • Candidate key: A candidate key is a unique identifier for each record in a table that can potentially be used as a primary key. It can be null and must be unique for each record.
  • Super key: A super key is a combination of one or more fields in a table that uniquely identifies each record. It can contain extraneous fields that are not necessary for uniqueness.
  • Alternate key: An alternate key is a candidate key that is not chosen as the primary key. It can be used as a unique identifier for each record in a table.

It is important to understand the different types of keys in a database to properly design tables and establish the necessary relationships between them.

Difference between 2-tier and 3-tier architecture in a DBMS

A 2-tier architecture in a DBMS involves a client and a server, where the client directly communicates with the server for database access. On the other hand, a 3-tier architecture involves a middle tier in between the client and server, where the middle tier manages communication between client and server and controls the flow of data. This design results in better scalability, security, and flexibility. In a 3-tier architecture, changes can be made to the middle tier without affecting the client or server, making it easier to maintain and update.

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