Indexing, Transactional, and Stored Procedure in Relational Database

Introduction.

How can I design a strong database schema?

But before we deep dive, what is a relational database and SQL and how does it work?

Basically, A relational database is a type of database that organizes data into one or more tables, where each table consists of a set of rows and columns. The columns represent attributes or fields of the data, while the rows represent individual records or instances of the data.

In a relational database, each table is connected to one or more other tables through a set of common fields, known as keys. This allows data to be organized and accessed in a structured way, making it easy to query and analyze large amounts of data.

Relational databases use a standardized language called SQL (Structured Query Language) to manage and manipulate the data stored in them. SQL allows users to create, update, and retrieve data from the database using commands such as SELECT, INSERT, UPDATE, and DELETE.

Some popular relational database management systems (RDBMS) include MySQL, Oracle, Microsoft SQL Server, and PostgreSQL. Relational databases are commonly used in a wide range of applications, from business and finance to e-commerce and social media.

Why it’s very important part of developing a new system?

Relational databases are an important part of developing a new system because they provide a structured and organized way to store, manage, and retrieve data. Here are some reasons why relational databases are so important in developing a new system:

1. Data organization: Relational databases provide a structured and organized way to store data, which is essential for managing large amounts of information in a way that is easy to understand and use. By organizing data into tables and rows, relational databases make it easy to query and manipulate data in a consistent and efficient way.
2. Data integrity: Relational databases enforce rules for data integrity, which ensures that the data stored in the database is accurate and consistent. This is important for preventing errors and ensuring that the system can be relied upon to provide accurate information.
3. Scalability: Relational databases are designed to be scalable, meaning that they can handle large amounts of data and users without sacrificing performance. This is essential for systems that need to handle large amounts of data or users.
4. Security: Relational databases provide robust security features, such as user authentication and access controls, which help to prevent unauthorized access to sensitive data. This is particularly important in systems that handle sensitive or confidential information.
5. Querying: Relational databases (SQL) rely on SQL to query data, which makes it easy to manipulate data using a standard language. NoSQL databases, on the other hand, typically use their own query language or APIs, which can make it more difficult to manipulate data using a standard language.
6. Performance: Relational databases (SQL) are highly optimized for transactional data, while NoSQL databases are optimized for handling unstructured data, making them a good choice for handling large amounts of data at high speeds.
7. Define relationships: In relational databases, relationships between tables are defined using primary and foreign keys. Primary keys are used to uniquely identify each record in a table, while foreign keys are used to link records across different tables.

What Is a Database Index, and What Does It Do?

In SQL, indexing is the process of creating a data structure that improves the speed of data retrieval operations on a database table. Indexes are similar to the indexes found in a book; they allow SQL to quickly locate and retrieve specific data within a table.

When a table is indexed, SQL creates a separate data structure that contains a subset of the columns in the table, along with a pointer to the original data in the table. This data structure is organized in a way that makes it faster and more efficient for SQL to search for specific rows of data based on the values in the indexed columns.

Indexes can improve the performance of SQL queries by reducing the amount of time required to scan a table and locate specific data. This is particularly important for large tables with many rows of data, where the time required to perform a full table scan can be significant.

However, indexing is not a panacea for database performance issues. Indexes can also have a negative impact on performance if they are not used correctly. Creating too many indexes, or creating indexes on columns that are rarely used in queries, can actually slow down database performance by adding unnecessary overhead to data retrieval operations.

It’s important to carefully consider which columns to index based on the types of queries that will be performed on the table. In general, columns that are frequently used in WHERE clauses, JOIN conditions, or ORDER BY clauses are good candidates for indexing.

Overall, indexing is an important tool for improving database performance in SQL. By carefully selecting the columns to index and maintaining indexes as data changes, you can ensure that SQL queries are executed quickly and efficiently, leading to better overall system performance.

The table indexing structure.

The top node of this tree structure is called the Root level. In fact, it starts from there and tries to find the entry by branching it to the right or left, as in the phone book example. There are Intermediate levels below the root level. While there should be one Root level, there can be several Intermediate levels depending on the amount of data in the table. At the bottom, there are Leaf Nodes, that’s to say, the structures that store the data. The search starts from the top and comes to the bottom level. The data stored in the leaf nodes will vary according to the index type.

CREATE INDEX idx_lastname
ON Persons (LastName);

CREATE UNIQUE INDEX index_name
ON table_name (column1, column2, ...);

What is a Database Transactional?

In database management systems, a transaction is a logical unit of work that contains one or more database operations. A transaction can be thought of as a sequence of actions that must be performed as a single, indivisible unit. Transactions are used to ensure the consistency, durability, and atomicity of database operations.

Consistency: Transactions ensure that the database is consistent both before and after the transaction. This means that any changes made to the database during a transaction must be consistent with the rules and constraints defined for the database.

Durability: Transactions ensure that once a transaction is committed, its changes are permanent and will survive system failures, power outages, or other unexpected events.

Atomicity: Transactions ensure that all database operations within a transaction are treated as a single unit of work. This means that if any part of the transaction fails, all changes made by the transaction are rolled back, and the database is returned to its original state before the transaction started.

For example, consider a bank transfer transaction. A bank transfer transaction typically involves two operations: deducting money from one account and adding money to another account. If these operations were not performed as part of a transaction, it would be possible for one operation to succeed while the other fails, leaving the database in an inconsistent state.

By using a transaction to group these operations, the bank can ensure that both operations are either completed successfully or both are rolled back in the event of a failure. This ensures that the database remains consistent, durable, and atomic.

In SQL, transactions are typically initiated with the BEGIN TRANSACTION statement and completed with either the COMMIT or ROLLBACK statement, depending on whether the transaction is successful or unsuccessful, respectively.

What is a Stored Procedure?

A stored procedure is a set of SQL statements that are stored in a database and can be executed later by calling them from an application or another stored procedure. They are typically used to encapsulate business logic or complex database operations that are reused across multiple applications or queries.

Stored procedures can help improve database performance by reducing network traffic and optimizing the way database transactions are handled. Because stored procedures are precompiled and stored in memory, they can execute faster than ad-hoc SQL statements that are executed on the fly.

Some benefits of using stored procedures include:

1. Improved performance: Stored procedures are compiled and stored in memory, which means they can be executed much faster than ad-hoc SQL statements.
2. Enhanced security: Stored procedures can be granted permissions separately from the underlying tables, which helps improve database security.
3. Encapsulated business logic: Stored procedures can be used to encapsulate complex business logic, making it easier to maintain and reuse across different applications.
4. Reduced network traffic: Stored procedures can help reduce network traffic by sending only the necessary data between the application and the database.
5. Version control: Stored procedures can be version-controlled, which makes it easier to track changes and roll back to previous versions if necessary.

The difference between the SQL statements and call procedure:

Create a stored procedure in MySQL

DELIMITER //
CREATE PROCEDURE stored_proc_tutorial.spGetAverageMarks(OUT average DECIMAL(5,2))
BEGIN
    SELECT AVG(total_marks) INTO average FROM studentMarks;
END //
DELIMITER

In conclusion, indexes, transactions, and stored procedures are all important components of a relational database system.

Indexes help improve query performance by providing a faster way to retrieve data from the database, especially when working with large datasets.

Transactions ensure that database operations are completed as a single logical unit of work, with either all changes being made successfully or none at all. This helps maintain the consistency and integrity of the data.

Stored procedures are a way to encapsulate complex business logic and database operations into a single, reusable unit. This can help improve database performance, security, and maintainability.

When designing a strong database schema, it is important to consider these factors and use them appropriately based on the specific needs of your application. By utilizing indexes, transactions, and stored procedures effectively, you can help ensure that your database is reliable, efficient, and secure.