Structure of DBMS with Diagram

The structure of Database Management System consists of various components that work together to keep managing and organizing the data in a structured manner. 

Block Diagram of DBMS Structure

Major Components of DBMS Structure:

The main components in DBMS structure as following them:

Users

In database management system (DBMS), users are categorized based on their interaction with the database. The main types of database users include:

Also Read: DBMS Architecture with Diagram and its Types

Database Administrator (DBA): Responsible for defining the database schema, controlling access to the database, ensuring security, monitoring system performance, and handling backup and recovery.

End Users: These are the individuals who interact with the database to retrieve, update, and modify data. They can be further classified into:

Naive/Parametric Users: They have limited knowledge of the DBMS but frequently use database applications to retrieve or input data.

Sophisticated Users: These are advanced users who write specialized database applications and interact with the system without directly writing programs.

Application Programmers/Specialized Users: They develop and maintain database applications, write queries, and interact with the database system using programming languages.

Temporary/Casual Users: These users have little knowledge of the DBMS and access the database occasionally to input or retrieve information.

Query Processor

The query processor in a database management system (DBMS) receives a query request in the form of SQL text, parses it, generates an execution plan, and completes the processing by executing the plan and returning the results to the client.

Primary Components of Query Processor

DML Compile: DML compiler in database management system (DBMS) has responsibility for translating Data Manipulation Language (DML) statements into low-level instructions that can be understood and executed by the query evaluation engine. It processes the DML statements into machine language instructions, enabling the execution of user requests.

Also Read: DBMS Features and Characteristics

The DML compiler is part of the query processor, which interprets and executes user queries. It also contains of sub-components, including the query parser, query optimizer, query executor, and storage engine

DDL Interpreter: The DDL (Data Definition Language) Interpreter is sub-component of the query processor in a database management system structure that helps to interpret the DDL statements such as schema definition statements like create, delete, etc. and stores the record in a data dictionary (in a table containing meta-data).

The DDL Interpreter has main duty for processing the DDL statements into a group of tables containing metadata (data about data) that is kept in the data dictionary. The DDL Interpreter also helps to execute the user requests that are received from the DML compiler.

Embedded DML Pre-Compiler: Embedded DML Pre-Compiler is a responsible to process Data Manipulation Language (DML) statements embedded in an application program into procedural calls. It converts DML statements in an application program to normal procedure calls in the host language. The pre-compiler interacts with the query processor to generate the appropriate code.

The DML Compiler processes DML statements into low-level instructions (machine language) that can be executed, while the DDL Interpreter interprets Data Definition Language (DDL) statements and records them in a set of tables containing metadata or data.

Query Evaluation Engine: A Query Evaluation Engine has main responsibility to execute the queries and producing the output of a given query. It works closely along with the Query Optimizer and the Query Execution Engine to optimize and execute queries efficiently.

The main functions of a Query Evaluation Engine include:

Query Optimization: The Query Optimizer translates the given query into a query execution plan, which is a program for an abstract machine inside the DBMS.

Query Execution: The Query Execution Engine takes the query execution plan and executes it, fetching data from the database and performing operations as specified in the plan. It interacts with the storage engine to retrieve and update data from tables and indexes.

Query Evaluation Plan Optimization: After selecting an evaluation plan, the system evaluates the query and produces the output of the query.

Query Processing: The Query Processing system involves parsing and translation of the query, optimization, and the actual execution of the query using the query evaluation plan.

Storage Manager

The Storage Manager is a crucial component in the structure of Database Management System (DBMS). It is responsible for managing the storage of data on the physical storage devices (such as hard drives or solid-state drives) and handling the interaction between the database and the storage media. The Storage Manager interacts with the Query Evaluation Engine to retrieve and update data from tables and indexes.

Primary Components of Storage Manager

Authorization & Integrity Manager: The Authorization and Integrity Manager in a Database Management System (DBMS) performs the following functions:

Also Read: 3 Tier Architecture in DBMS with Diagram

Authorization Manager: It ensures role-based access control by checking whether a particular user is privileged to perform the requested operation. This is enabling with identifying the user, checking their privileges; as well as providing access depending on their roles and privileges.

Integrity Manager: It tests for the satisfaction of integrity constraints and ensures that the operations on a particular part of the data do not affect the other stored data. It is getting main focuses on avoiding the accidental changes to the data and keeping to maintain data integrity.

Transaction Manager: Transaction Manager is responsible for making ensure that the database remains in a consistent state despite system failures and those transactions are executed in an all-or-nothing fashion. It manages transactions, which are a set of operations used to perform a logical set of work.

Transactions are executed as a single unit, and if the database operations do not update the database but only retrieve data, this type of transaction is called a read-only transaction. The Transaction Manager ensures that transactions are atomic, consistent, isolated, and durable (ACID properties).

File Manager: The File Manager in DBMS structure is responsible for managing the allocation of space on disk storage, maintaining the list of structures and indices described in the internal schema, and managing the physical storage of data on disk and in memory.

It is responsible for file system integrity, file sharing and collaboration, file metadata management, file space allocation, and file location and access policies. The File Manager interacts with the operating system of the host computer or has a file subsystem written especially for the DBMS

Buffer Manager: Buffer Manager in Database Management System is responsible for allocating space in the main memory to store data temporarily. It also helps to manage the database buffer that works as middleware in between the programs getting to access the data and the physical storage devices. The Buffer Manager has the responsibility for several tasks like as allocating space for the database buffer, sending the block address whenever the user sends a request certain data, allocating data blocks in the database buffer, and deleting the older blocks from the buffer when space is required for new data blocks.

Disk Storage

The disk storage is a critical component DBMS that is responsible for managing space on disk, mapping pages to locations on disk, loading pages from disk to memory, and saving pages back to disk. It is further divided into sub categories, including:

Primary Components of Disk Storage

Data Files: Data files are used to store actual data or a view of the data. Records in data files are organized into members, and the files are typically stored in binary format on disk drives, which are formatted into blocks to store the records.

Also Read: 2 Tier Architecture in DBMS with Examples

Data files in a DBMS contain data and objects such as tables, indexes, stored procedures, and views, while log files contain information required to recover all transactions in the database.

Data Dictionary: Data dictionary is a group of names, attributes, and definitions about data elements that are being utilised in database and information system. It explores the meanings and objectives of data elements along with the context of the project and offering the guidance on interpretation, representation, and accepted meanings.

Data dictionaries are most helpful for preventing the data inconsistencies, defining conventions, and providing the consistency in data collection and use that help to make the data easier to analyze, and enforcing data standards

Indexes: In Database System structure, indexes are data structures used to efficiently retrieve records from database files based on specific attributes. There are several kinds of indexes in DBMS, like as primary, secondary, clustered, and non-clustered indexes.

Indexes are structured in a way that the search key, which is the first column of the index, contains a duplicate or copy of the table’s candidate key or primary key. The primary key values are saved in sorted order, allowing related data to be quickly accessible. The data reference, which is the second column of the index, contains pointers to the actual data location on the disk.

Statistical Data: Statistical database is a database used for statistical analysis purposes, and it is an Online Analytical Processing (OLAP) system rather than an Online Transaction Processing (OLTP) system. Statistical databases consist the parameter data and measured data for these parameters that are often utilised for population statistics and in industries to make informed decisions.

They can be created using SQL, as long as the data is structured in a way that allows for aggregated queries, such as counts and averages.

Difference between DBMS Structure and DBMS Architecture

Here, we will show you all the key differences between DBMS structure and DBMS architecture:

FAQs (Frequently Asked Questions)

How is data organized in a DBMS structure?

Data is organized in tables, each consisting of rows and columns. Relationships in between the tables are established by using keys, and constraints ensure data integrity.

What is the difference between logical and physical DBMS structure?

The logical structure defines how data appears to users and is represented conceptually, while the physical structure involves the actual storage details and how data is stored on the storage media.

Why is normalization important in DBMS structure?

Normalization allows eliminating data redundancy, minimizing update anomalies, and enhancing data integrity by getting to organize data into well-structured tables.

How does DBMS structure support data integrity?

DBMS structure is getting to support data integrity via the using of constraints, including primary keys, foreign keys, unique constraints, and check constraints that enforce rules on the data.

How does DBMS structure differ in various database models?

DBMS structure can vary based on the database model (e.g., relational, hierarchical, network). Each model has its own way of organizing and representing data.

Bottom Lines

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Also Read: Advantages and Disadvantages of DBMS (Database Management System)

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