Indexing in Database

Question

How does indexing impact query performance in large datasets?

Tuhin Paul · Answer

Here is a high level overview of the indexs :

Tuhin Paul · Answer

Check this article good to get started: https://www.c-sharpcorner.com/article/understanding-sql-server-indexes-and-their-performance-implications/

Muhammad Imran Ansari · Answer

Indexing significantly improves query performance in large datasets by allowing the database to quickly locate and retrieve specific rows without scanning the entire table. It speeds up SELECT queries WHERE clauses JOIN operations and sorting (ORDER BY GROUP BY). However indexes consume additional storage and can slow down write operations (INSERT UPDATE DELETE) since they need to be updated. Proper indexing strategies such as creating indexes on frequently queried columns and avoiding over-indexing are essential to balance read performance and write efficiency. Regular monitoring and maintenance of indexes are also crucial for optimal database performance.

Sam Hobbs · Answer

In a simplified explanation of what indexes are they are portions of a table stored in memory with a pointer to where the data is at in the database. An index might be every key value such as an account number along with the exact location in the database of the rest of the record. Or the index might be selected key values that indicate where to start looking (sequentially) in the database. Without an index the database system might need to search sequentially from the beginning to find the data.

Shubham Sidnale · Answer

Indexing in Database Indexing is a database optimization technique that improves the speed of data retrieval operations on a table by reducing the number of disk accesses required. It works like a book index allowing the database engine to locate data quickly without scanning the entire table. Types of Indexes Clustered Index Determines the physical order of data in the table. Only one per table . Example: A primary key automatically creates a clustered index. Real-time Example: In an employee table if the EmployeeID (Primary Key) is a clustered index data is physically sorted by EmployeeID. Non-Clustered Index Creates a logical order using pointers to actual data. Multiple indexes per table are allowed. Example: An index on Name or Email in an employee table. Real-time Example: Searching an employee by Email—a non-clustered index helps in faster lookups. Unique Index Ensures no duplicate values in the indexed column. Example: An index on Email to prevent duplicate entries. Composite Index Index on multiple columns together. Example: (FirstName LastName) for efficient searches on full names. Full-Text Index Used for fast searching of text data in large documents. Example: Searching within product descriptions in an e-commerce database. Real-Time Example (E-commerce Database) Consider a Products table: ProductID (PK) ProductName CategoryID (FK) Price 101 Laptop 1 700 102 Mouse 2 20 103 Keyboard 2 30 Clustered Index on ProductID (Primary Key) → Data is physically sorted by ProductID. Non-Clustered Index on ProductName → Faster search by name instead of scanning all records. Composite Index on (CategoryID Price) → Optimizes queries filtering by Category and sorting by Price . Benefits of Indexing Faster Search – Reduces query execution time. Efficient Sorting & Filtering – Optimizes ORDER BY & WHERE queries. Improved Performance – Minimizes disk I/O operations. Drawbacks Slower Insert/Update/Delete – Indexes need to be updated. Consumes More Storage – Additional space required. Best Practice: Use indexes wisely on frequently searched columns but avoid over-indexing!