Understanding DBMS Architecture: Types, Examples, and Advantages

Data is generated with every digital activity on a daily basis. A database is a system for storing, managing, and retrieving data. It organises information in a way that makes it easy to access and use for various applications. For this article, we need to understand two types of databases: 

Centralised Databases

In a centralised database, all data is stored in a single location, such as a server. Users can access this database through a network. Because everything is in one place, centralised databases are easier to manage and secure. However, if the server fails, the entire system may stop working. One example is a bank storing all of its customer data on a central server. 

Decentralised Databases

A decentralised database stores data across multiple locations or servers. Each server holds part of the data and works independently. This system is more reliable because even if one server fails, others continue to function. However, managing decentralised databases can be more complex. A good example is a blockchain network where data is distributed across many nodes.

The DBMS architecture refers to the structural design and interconnected components that manage and maintain databases efficiently. One widely used approach is the client-server architecture, where client and server components are separated to streamline data handling, application logic, and user interactions.

At the heart of any database system structure are several essential components:

Disk Storage

Disk storage is a critical component of a database management system (DBMS). It stores data permanently, ensuring it's accessible even after a system shutdown. Efficient use of disk storage is key to managing, retrieving, and organising large datasets. Disk storage in DBMS involves:

1. Data Files: Data files hold the actual user data in a structured format. These files store all the records, transactions, and information required by the application. They are designed for optimised storage and fast retrieval.
2. Data Dictionary: The data dictionary is also known as metadata storage and contains detailed information about the database structure. It records table names, column types, constraints, and relationships. This acts as a reference for the DBMS so it can understand how data is organised and used.
3. Indices: Indices are like shortcuts for data access. They create pointers for specific rows or records, which enables the DBMS to locate data quickly without scanning the entire database. Indices are necessary to greatly improve query performance and are especially needed for large datasets.

Query Processor

The query processor is an important component of a DBMS. It interprets user queries and executes them precisely. The query process involves several specialised components that handle different tasks to convert high-level queries into low-level instructions.

1. DML Compiler: The Data Manipulation Language (DML) compiler processes user commands like SELECT, INSERT, UPDATE, and DELETE. It converts these high-level queries into low-level instructions that the DBMS can understand and execute.
2. DDL Interpreter: The Data Definition Language (DDL) interpreter handles statements like CREATE, ALTER, and DROP. It processes commands that define or modify the structure of the database, such as creating tables or changing column properties.
3. Embedded DML Pre-compiler: integrates DML statements into programming languages like C, Java, or Python. It translates embedded SQL queries into a format that the DBMS can process. It is necessary to maintain proper communication between applications and the database.
4. Query Optimizer: The query optimiser is responsible for improving query performance. It evaluates multiple ways to execute a query and selects the most efficient one. This reduces processing time, so the query execution is done quickly.

Storage Manager

The storage manager is an essential part of a database management system. It handles how data is stored, retrieved, and managed on physical storage devices like disks. The storage manager is responsible for data integrity, security, and efficient access. It includes the following key components:

1. Authorisation Manager: It’s a check that only lets authorised users access or modify the database. It verifies user credentials and permissions to prevent unauthorised access, so the database is secure.
2. Integrity Manager: The integrity manager enforces rules that maintain the correctness of the data. For example, it ensures no duplicate primary keys exist and that foreign key constraints are followed. This prevents invalid or inconsistent data from entering the database.
3. Transaction Manager: oversees all database transactions. It oversees that each transaction is completed fully or not at all which is needed for maintaining the database's reliability. This includes handling operations like rollbacks in case of failures and maintaining data consistency.
4. File Manager: The file manager organises and manages data on physical storage devices. It handles how data files are created, read, and written. This component is necessary for efficient storage utilisation and supports large-scale data management.
5. Buffer Manager: The buffer manager controls the flow of data between main memory (RAM) and disk storage. It stores frequently accessed data temporarily in memory to speed up data retrieval and reduce disk access time.

Concurrency control

Concurrency control enables multiple users to access a database at the same time without causing errors or data issues. It prevents problems like data loss, inconsistencies, or system crashes by managing how transactions are handled. A transaction, which is a single logical unit of work that retrieves or modifies data can cause delays if executed one at a time. This increases the waiting time for other transactions and slows overall performance. To improve throughput and reduce delays, transactions are executed concurrently. It allows the database to handle multiple tasks efficiently. 

Together with communication interfaces and concurrency control mechanisms, these components form the backbone of relational database architecture. They work in harmony to ensure seamless user interactions, secure data access, and efficient database operations.

A Database Management System (DBMS) is organised into three main levels: the Internal Level, the Conceptual Level, and the External Level.

1. Internal Level
   This level handles the physical storage of data within the database. It focuses on how data is stored and retrieved from storage devices, such as hard drives or solid-state drives. The internal level is responsible for low-level operations like data compression, indexing, and managing storage allocation.
2. Conceptual Level:
   The conceptual level represents the logical organisation of the data. It defines the structure and relationships between data elements, including tables, attributes, and their links. This level is independent of any specific DBMS and ensures that the data schema can be used across different systems without affecting the underlying database implementation.
3. External Level:
   This level represents how users interact with the database. It defines the user’s view of the data and presents it in a way that is meaningful to them. Users can access the database through customised views or interfaces that focus on their specific needs. They can do all this without being concerned about the database's internal structure or logic.

Database Architecture vs. Tier Architecture

Database architecture refers to the overall design and structure of a database system. It involves how data is organised, stored, managed, and accessed within the system. The important elements of the architecture of database are data models, components like the DBMS, and how different layers, such as the storage manager, query processor, etc., interact to provide data management and access.

On the other hand, tier architecture refers to the way a database system is structured. This structure is defined by how its components are distributed across different layers. In tier architecture, the database is divided into multiple layers, such as single-tier, two-tier, or three-tier systems. These tiers create separation of the user interface, application logic, and database to improve scalability, security, and maintenance.

The main difference to remember between the architecture of database and tier is that database architecture focuses on the structure and components of the database system itself. The tiered architecture deals with how these components are distributed across different layers.

Database management systems (DBMS) are designed with multiple levels of abstraction to ensure efficient functioning. These layers help define the structure and operation of the DBMS architecture.

Since users and applications do not always interact directly with the database, various architectures of a database system are used based on how users are connected. These architectures are tier-based, meaning the architecture of DBMS is categorised by the number of layers within its structure.

For instance, in an n-tier DBMS architecture, the system is divided into n independent layers:

• 1-tier architecture in DBMS has a single layer where the database and user interface coexist.
• Two-tier DBMS architecture separates the system into two layers, typically a client and a server.
• Three-tier architecture introduces a middle layer, such as an application server, for additional processing.

As the number of layers increases, the level of abstraction also increases, enhancing security and adding complexity to the database system structure. Each layer in the application architecture in DBMS operates independently. Therefore, modifications to one layer do not affect the others, ensuring flexibility and maintainability in the system design. Let’s look at each one in more detail:

1. Single Tier Architecture in DBMS

In single-tier architecture in dbms, the database is directly accessible to the user. The user interacts with the DBMS architecture directly, making changes that immediately reflect on the database. This architecture does not offer user-friendly tools for end-users and is ideal for local application development where programmers need quick, direct access to the database.

This type of architecture of a database system is best suited for scenarios where:

• Data is rarely modified.
• Only a single user is accessing the database.
• A straightforward way to interact with or modify the database is required.

Example:
When learning Structured Query Language (SQL), developers often install an SQL server and set up a database on their local machine. This allows direct execution of SQL queries without a network connection. This setup is a 1-tier architecture in DBMS.

Advantages of Single-Tier Architecture:

1. Simplicity: Easy to set up since it only requires a single machine.
2. Cost-Effective: No need for additional hardware, making it budget-friendly.
3. Easy Implementation: Quick deployment, making it ideal for small projects or development environments.

2. Two-Tier Architecture in DBMS

In two-tier architecture, the system follows a basic client-server architecture. The client-side applications directly communicate with the server-side database using APIs like ODBC (Open Database Connectivity) or JDBC (Java Database Connectivity). The user interface and application logic run on the client side, while the server handles tasks like query processing and transaction management. In this DBMS architecture, the client application establishes a connection to the server to interact with the database.

API Call 

APIs in the architecture of database act as intermediaries which allow the client to send requests to the server for tasks like getting, updating, or removing data. They convert simple commands from the client into instructions the database can understand. API makes it easy to work with different databases through standardisation and also keeps the connection secure by including features for authentication and encryption.

Example:
Imagine withdrawing cash at a bank. The banker enters your account details and withdrawal amount into the system. The client application (banker’s interface) sends a request to the server-side database to check your balance and process the transaction. This setup is a classic example of two-tier DBMS architecture.

Advantages of Two-Tier Architecture:

1. Supports Multiple Users: Suitable for organisations as multiple users can access the database simultaneously.
2. High Processing Power: The server handles database functions, improving performance.
3. Faster Access: Direct connection between client and server ensures quick data retrieval.
4. Easy Maintenance: With two distinct layers, updates and maintenance become simpler.

3. Three-Tier Architecture in DBMS :

In a three-tier architecture, there is an additional layer between the client and the server, known as the application server. The client does not directly communicate with the database. Instead, client-side applications interact with the application server, which then communicates with the database server. This layer of separation ensures that the end-user is unaware of the database's internal details, and the database remains insulated from direct client interactions.

Working of Application Layer 

The application layer acts as an intermediary between the client and the database. It processes requests from the client, then performs necessary business logic, and finally sends the appropriate queries to the database. This separation keeps the client only with the application layer, and hence, it keeps the database secure and independent from direct user interactions.

Example:
Consider an online shopping platform like Amazon. When a user places an order, the client-side interface (website or app) sends the request to an application server. The application server processes the order, verifies stock availability, and updates the database accordingly. The client never communicates directly with the database; the application server handles all interactions.

Advantages of Three-Tier Architecture:

1. Scalability: The application server can manage load balancing, allowing support for numerous clients without impacting database performance.
2. Data Integrity: The application layer filters and validates client requests, reducing the risk of data corruption or erroneous queries.‍
3. Security: By removing direct access to the database, the architecture minimises the chance of unauthorised access and enhances security.

DBMS architecture must be understood by students who hope to become software developers. It gives an understanding of how data is structured, retrieved, accessed and utilised, and it also bestows the foundation on which all computer-related ideas, such as networking, system design and applications, are developed. Understanding single-tier, two-tier, and three-tier architectures lets students understand how different application programs work in practice. To learn more and build your knowledge, join the CCBP Academy 4.0 program.

1. What is DBMS architecture, and why is it important?

DBMS architecture refers to the design and structure of a database system, which determines how data is stored, accessed, and managed. It’s important because it helps optimise performance, security, and scalability based on the needs of different applications.

2. What are the main types of DBMS architecture?

The main types of DBMS architecture are Single Tier Architecture, Two Tier Architecture (Client-Server), and Three Tier Architecture. Each type varies in complexity, use case, and how users interact with the database.

3. How does Two Tier Architecture differ from Three Tier Architecture?

In Two Tier Architecture, the client communicates directly with the database server. In Three Tier Architecture, an intermediate application server handles communication between the client and the database, providing better security and scalability.

4. What factors determine the choice of DBMS architecture?

Factors include the number of users, database size, data access frequency, security needs, and application complexity.

5. How does understanding DBMS architecture help in software development?

Understanding DBMS architecture helps developers design efficient, secure, and scalable applications by choosing the right structure for data management and optimising interactions between clients, servers, and databases.