Types of Views in SQL: Why They Matter More Than You Think!

Key types of views in SQL include simple views, complex views, materialized views, and inline views. Each type serves specific needs by simplifying queries, improving performance, or securing sensitive data. These views allow developers and analysts to access the right data slice without altering the original tables.

Understanding the types of views in SQL is essential for building efficient queries, enforcing data security, and maintaining clean and modular database designs.

In this blog, we’ll explore types of views in SQL and cover how to create, modify, and use them efficiently with performance and access control tips.

Types of Views in SQL: An Overview

SQL offers different types of views to support data abstraction, security, and performance optimization. Simple views display selected columns from a single table, making queries easier and hiding sensitive data. Complex views involve joins, subqueries, or aggregations to present complicated logic in a simplified way.

Materialized views store a query's results physically, which improves performance when dealing with expensive or large computations. Inline views, used as subqueries in the FROM clause, help break down and organize complex queries. These views allow developers to tailor data access based on application needs, user roles, and system efficiency.

In 2025, professionals using SQL to improve business operations will be in high demand. If you're looking to develop relevant SQL skills, here are some top-rated courses to help you get there:

• Executive Post Graduate Certificate Programme in Data Science & AI
• Executive Diploma in Data Science & AI with IIIT-B
• Master’s Degree in Artificial Intelligence and Data Science

Let’s take a closer look at the different types of views in SQL and how each one can simplify your data tasks.

What Are the Different Types of Views in SQL?

Some types of views in SQL rely on calculations that run each time, while others hold separate copies behind the scenes. They all share one goal: keep your queries concise and your project organized.

Choosing the right type can reduce overhead when filtering or combining data. Below is a closer look at the main types of views in DBMS you might use, along with their strong points.

1. System-Defined Views

System-defined views are prebuilt by the database system and monitor and manage internal components such as databases, tables, and performance metrics. They help you check metadata without digging into raw system tables. These views give insights into everything from structure to user activity and are perfect for administrators or developers needing visibility into the backend. You don't need to create them. They’re always available and ready to query.

Sample Query:

SELECT name, database_id, create_date
FROM sys.databases;

Query Explanation: This query retrieves a list of all databases the SQL Server manages. It shows each database's name, unique identifier (ID), and the date it was created.

Output: You will see the names of all databases, their ID numbers, and the date each one was created.

Are you a full-stack developer wanting to integrate AI into your workflow? upGrad’s AI-Driven Full-Stack Development bootcamp can help you. You’ll learn how to build AI-powered software using OpenAI, GitHub Copilot, Bolt AI & more.

Also Read: SQL for Data Science: Functions, Queries, and Best Practices

Let’s explore the main categories of system views, how they work, what kind of data they provide, and how to use them with examples.

1. Information Schema Views

Information Schema Views are standardized views that provide details about the database's structure, such as tables, columns, constraints, and data types. They are ANSI SQL compliant and start with the prefix INFORMATION_SCHEMA. These views are invaluable when building cross-platform database tools or checking table designs without using system-specific SQL.

They work by reading metadata from your database in a portable and easy-to-query way, giving you insight into the architecture of your tables and columns without digging into proprietary system catalogs.

Sample Query

SELECT COLUMN_NAME, DATA_TYPE  
FROM INFORMATION_SCHEMA.COLUMNS  
WHERE TABLE_NAME = 'YourTableName';

Query Explanation: This query retrieves all column names and their data types from the specified table (YourTableName) using the INFORMATION_SCHEMA.COLUMNS view. It helps developers or database admins understand what data each column stores, such as VARCHAR, INT, or DATE, without directly accessing internal SQL Server tables.

Sample Output:

Also read: Is SQL Hard to Learn? Breaking Down the Challenges and Solutions

2. Catalog Views

Catalog views give you direct access to detailed metadata stored within the database engine, such as information about tables, columns, constraints, triggers, and indexes. They are more powerful than information schema views and are unique to SQL Server. These views pull from system base tables but present the data in an easier-to-understand structure.

Catalog views help you manage database objects more effectively. They help check indexes, triggers, and other metadata. You can use them to perform audits or write scripts for schema changes. These views give deeper access to SQL Server’s internal details.

Sample Query

SELECT name, object_id  
FROM sys.tables;

Query Explanation: This query uses the sys.tables catalog view to list all user-defined tables in the current database. For each table, it displays the table name and its object_id, which is a unique identifier used internally by SQL Server. These IDs are valid when joining other system views to get more metadata.

Sample Output:

3. Dynamic Management Views (DMVs)

Dynamic Management Views (DMVs) provide real-time diagnostic and monitoring information about your SQL Server instance. They help administrators track session activity, resource usage, query performance, and server health. These views are essential for troubleshooting issues, monitoring server behavior, and optimizing performance.

DMVs collect data dynamically from memory and internal processes. Unlike other views, which show static schema metadata, they reflect current runtime conditions.

Sample Query

SELECT session_id, connect_time, host_name  
FROM sys.dm_exec_connections;

Query Explanation: This DMV query lists all current database connections. It shows the session_id (unique to each connection), the time each connection was established, and the name of the client machine (host_name) that initiated it. This is useful for identifying active users, connection history, or potential unauthorized access.

Sample Output:

2. User-Defined Views

User-defined views are custom views you create to show only the needed data. They help simplify complex queries, limit access to sensitive columns, and make data easier to understand.

Sample Query

CREATE VIEW EmployeeBrief  
AS  
SELECT EmployeeID, FullName, Department  
FROM Employees  
WHERE IsActive = 1;

Query Explanation: It selects only active employees from the Employees table, limiting the result to relevant columns. Since it uses a single table and no aggregation or joins, it’s easy to update through this view. It helps streamline queries and protect data by hiding unused fields from the user.

Output:

Let’s explore the main types of user-defined views in SQL, understand how they work, what kind of data they provide, and how they’re used through examples.

1. Simple Views

Simple views are based on a single table and do not include joins, group functions, or complex calculations. They enable you to display filtered or specific columns from a table in a clean and focused way. Simple views are easy to maintain and helpful when controlling access to specific rows or columns from a large table.

They act like virtual tables, returning a saved query result every time you run them, simplifying repetitive query logic.

Sample Query:

CREATE VIEW ActiveJobs  
AS  
SELECT JobID, Title, Department  
FROM JobOpenings  
WHERE IsOpen = 1;

Query Explanation: This view is created on a single table, JobOpenings. It selects only the active job positions (IsOpen = 1), showing just the JobID, Title, and Department fields. You can now simply use SELECT * FROM ActiveJobs to view open jobs without needing to filter each time.

Sample Output:

2. Complex Views

Complex views combine data from multiple tables using JOIN, GROUP BY, or aggregate functions. These views help generate meaningful insights, such as totals, averages, or cross-table summaries. They're great for reporting, dashboards, and consolidated overviews.

They run like a saved multi-table query and return up-to-date calculated data whenever accessed.

Sample Query:

CREATE VIEW ClientRevenue  
AS  
SELECT c.ClientName, SUM(t.Amount) AS TotalRevenue  
FROM Clients c  
JOIN Transactions t ON c.ClientID = t.ClientID  
GROUP BY c.ClientName;

Query Explanation: This view joins the Clients and Transactions tables to display the total revenue generated by each client. The view groups the transaction data by client name and calculates the total amount using the SUM() function.

Sample Output:

3. Inline Views

Inline views are subqueries placed directly inside the FROM clause of a query. They're not permanent views but work like temporary views within a single SQL statement. They help break complex logic into manageable pieces.

They’re helpful when you need temporary transformations or filtering before applying additional logic in the outer query.

Sample Query:

SELECT RegionName, AvgSales  
FROM (  
  SELECT RegionName, AVG(SalesAmount) AS AvgSales  
  FROM RegionalSales  
  GROUP BY RegionName  
) AS RegionStats  
WHERE AvgSales > 10000;

Query Explanation: The inner query calculates average sales (AvgSales) for each region. The outer query filters this data to show only regions where average sales exceed ₹10,000. This structure is ideal for reducing query nesting and improving readability.

Sample Output:

4. Materialized Views (Indexed Views in SQL Server)

Materialized views (or Indexed Views in SQL Server) store the result set of a view physically on disk. Unlike regular views, which execute their queries every time they are accessed, materialized views store precomputed data, which improves performance for expensive queries.

These are ideal for scenarios involving large aggregations, frequent reporting, or performance-heavy joins.

Sample Query:

CREATE MATERIALIZED VIEW ProductTotals  
AS  
SELECT ProductID, SUM(QuantitySold) AS TotalSold  
FROM SalesHistory  
GROUP BY ProductID;

Query Explanation: This materialized view calculates and stores total units sold for each product by summarizing the SalesHistory table. The data is refreshed on demand or on a set schedule, making it fast to access, especially in analytical environments.

Sample Output:

5. Partitioned Views

Partitioned views combine multiple tables (usually with similar structures) into one logical view. Each table typically represents a segment or "partition" of the data, such as sales by quarter, region, or department. These views are used to manage and query large datasets efficiently.

They use UNION ALL to merge tables with identical schemas into a single result set.

Sample Query:

CREATE VIEW AllSales  
AS  
SELECT * FROM Sales_Q1  
UNION ALL  
SELECT * FROM Sales_Q2  
UNION ALL  
SELECT * FROM Sales_Q3  
UNION ALL  
SELECT * FROM Sales_Q4;

Query Explanation: This partitioned view merges sales data from four quarterly tables into a single unified view. It simplifies querying full-year sales without running separate queries for each quarter.

Sample Output:

Now that we understand views and their types, let's explore how different types of views in a DBMS work behind the scenes.

How Do Different Types of Views in DBMS Work Internally?

A view looks like a regular table but does not store data. Instead, it runs a saved SELECT query each time you access it, showing the most current information from the original tables. Unlike a physical table, which keeps data on disk and updates it directly, a view only displays results when needed. This helps save storage and ensures you always see up-to-date data, making views useful for reporting, filtering, or hiding sensitive information.

Here is a brief outline of how they operate:

• Instant Reflection: A query on a view pulls the latest records from its underlying data source.
• Defined by SELECT: The logic in the defining SELECT statement decides which rows and columns appear.
• No Direct Record Management: You adjust real data in the base table; the view only reflects those changes.
• Indexing: An indexed or materialized view can store results for quicker queries, but it refreshes according to the settings you choose.

Also Read: The Essential Guide To Understanding SQL In DBMS

Are you interested in knowing how to structure, create, and manage databases using MySQL? upGrad’s free Introduction to Database Design with MySQL course covers ER models, normalization, SQL queries, and relational schema concepts.

Also Read: SQL For Beginners: Essential Queries, Joins, Indexing & Optimization Tips

Next, let’s look at how you can work with the types of views in SQL.

How Do You Create, Alter, and Drop Views?

Design requirements may shift as your database evolves, so having a clear way to introduce, revise, or remove views is fundamental. Each process involves distinct SQL commands that ensure you retain control over how data is exposed and manipulated. 

Despite minor syntax variations between database systems, the main actions stay consistent: you pick a name for the view, define its columns or conditions, and then either update or drop it as you see fit.

Below is a roadmap for setting up a brand-new view, modifying existing ones, and removing irrelevant ones.

1. CREATE VIEW Syntax and Examples

The CREATE VIEW command gives you a single reference point for a query that might otherwise be repeated multiple times. You can form a view based on one table or unify data from multiple sources into a logical entity. You are free to filter rows, rename columns, or even combine data from multiple tables. 

Let’s walk through the basic pattern, then see an example.

Below is a snippet that showcases the core syntax:

CREATE VIEW view_name AS
SELECT column1, column2, ...
FROM table_name
WHERE condition;

This template outlines how you declare your view, specify the columns to include, and optionally apply conditions like WHERE to limit rows. For instance, a single-table view might only show records meeting certain criteria, while a multi-table definition could join multiple sources in one place.

You can also rename columns within the SELECT statement to make your view more intuitive. For example:

Sample Query:

CREATE VIEW EmployeeOverview
AS
SELECT EmployeeID AS ID, FullName AS Name
FROM StaffRecords
WHERE IsActive = 1;

Query Explanation: In this scenario, the table StaffRecords has columns named EmployeeID and FullName, but the view presents them as ID and Name. You also filter out inactive employees by using a WHERE clause. Anyone querying the EmployeeOverview view sees a narrowed, user-friendly version of the table.

Output: 

2. Updating a View Definition

Sometimes, a view needs to reflect a shifting reality, like when new columns appear in the base table, or your naming conventions change. Editing a view requires redefining it by default, so many databases offer a CREATE OR REPLACE VIEW statement to streamline the process. 

Below is a snippet that adds a column to an existing view:

Sample Query:

CREATE OR REPLACE VIEW EmployeeOverview
AS
SELECT EmployeeID AS ID, FullName AS Name, Department
FROM StaffRecords
WHERE IsActive = 1;

Query Explanation: The main difference here is the OR REPLACE phrase, which instructs the database to keep the same name (EmployeeOverview) but swap in the new definition. This helps maintain references or permissions already granted on the view. 

However, check whether the new definition aligns with existing queries or applications. Adding columns may be simpler than removing them since dependent queries might break if columns suddenly vanish.

Output:

When revising views, consider the following:

• Ensure the base tables still contain the columns you want to add.
• Confirm the WHERE clause and any joins remain logical in your new context.
• Retest any stored procedures or user queries that rely on the original view.

3. Dropping a View

If a view has outlived its purpose or needs to be replaced entirely, you can remove it. This is done with a simple DROP VIEW command, which stops the database from maintaining a definition under that view name.

Below is the relevant snippet:

DROP VIEW EmployeeOverview;

Query Explanation: The DROP VIEW statement deletes the view named EmployeeOverview from the database. After this command is executed:

• The view no longer exists.
• Any queries that try to access EmployeeOverview will result in an error.
• This does not affect the underlying table (StaffRecords); only the view is removed.

When you try to access the table with this command:

SELECT * FROM EmployeeOverview;

Output: You will get an error like:

Msg 208, Level 16, State 1: Invalid object name 'EmployeeOverview'.

When you drop a view:

• Any queries or applications pointing to the view will fail if they are not updated.
• Permissions granted directly on that view also vanish since the object no longer exists. 

Make sure no vital dependencies remain before you run this command, especially in production environments. If a view is crucial to ongoing operations, dropping it could break a range of front-end or reporting tasks.

4. Listing All Views

It can be helpful to see which views exist, especially in larger databases. Different systems offer various ways to look up existing views. Some platforms let you run a statement like SHOW FULL TABLES to spot entries labeled as views, while others use catalog or information schema tables for that purpose.

Below is a short snippet that references system metadata to list every view in your current database:

Sample Query:

SELECT table_name
FROM information_schema.views
WHERE table_schema = 'YourDatabaseName';

Query Explanation: This query lists the names of all views available in a specific database (YourDatabaseName) by checking the INFORMATION_SCHEMA.VIEWS system view.
Here’s what each part does:

• information_schema.views: A system-defined view that stores metadata about all user-defined views.
• table_schema = 'YourDatabaseName': Filters the views to only those that belong to the database/schema you specify.
• table_name: Returns the name of each view in that schema.

Also Read: Stored Procedure in SQL: How to Create, Executive, Modify, Types & Use Cases

Now, let’s look at when you can edit data using the different types of views in SQL.

upGrad’s Exclusive Software and Tech Webinar for you –

SAAS Business – What is So Different?

When Can You Update, Insert, or Delete Data Through a View?

Some types of views in SQL allow you to run data manipulation language (DML) commands such as UPDATE, INSERT, or DELETE without directly touching the underlying tables. This means you can change the underlying table through the view, but only under specific conditions. This feature is useful when you want to interact with a filtered or simplified version of the data, without accessing the full table directly.

However, not all views are updatable. The structure and definition of the view determine whether you can modify data through it. Knowing these rules can save you time and prevent errors when managing database records.

Conditions for an Updatable View

Views that let you modify underlying data must meet certain requirements. Here is a brief list of conditions:

• No GROUP BY or DISTINCT: Including these features aggregates rows or removes duplicates, which prevents direct row-level updates.
• Single Base Table: The view can only reference one table in its FROM clause. If more tables join in, the view usually becomes read-only.
• Primary Key in Base Table: A key column helps the system identify which exact row you are targeting when you run an update.
• No Derived or Calculated Columns: Columns produced by expressions, functions, or subqueries are not writable.

1. Updating Data in a View

Some updatable views let you change values in the underlying table without opening multiple objects. If the conditions above are satisfied, your changes automatically flow back to the real data.

Below is a snippet that demonstrates how to update a record through a view. There are no extra columns beyond what’s stored in the base table, so the update works:

UPDATE ActiveJobs
SET Department = 'Technology'
WHERE JobID = 101;

Query Explanation: When you run this statement, the system locates the corresponding row in the JobOpenings table (referenced by the ActiveJobs view) and sets its Department to 'Technology'. This approach helps you keep your code centralized if your view has already filtered out irrelevant rows.

Output: The Department value is updated only if the ActiveJobs view is based on a single table, contains no GROUP BY, and allows updates.

If the view is not updatable, it's based on joins, has GROUP BY, etc, the query will throw an error

2. Inserting Rows Through a View

When a view includes all the required columns (especially those marked NOT NULL in the base table), you can insert new records by treating the view almost like a direct table reference.

Below is a snippet that adds a fresh job posting via the same ActiveJobs view. Keep in mind that you must include columns for any fields that do not accept null values.

Sample Query:

INSERT INTO ActiveJobs (JobID, Title, Department, IsOpen)
VALUES (202, 'Lead Designer', 'Design', 1);

Query Explanation: This SQL query inserts a new row into the ActiveJobs view, adding a job listing for the position of "Lead Designer" in the Design department. It sets IsOpen to 1, meaning the job is active. If the view is updatable and based on a single table without complex logic (such as joins or aggregates), the insert will be reflected in the underlying base table.

Output:

3. Deleting Rows Through a View

The DELETE operation works if the view is directly tied to one base table. In a multi-table scenario, the database cannot determine which physical rows to remove reliably.

Here is a snippet that deletes a row through the ActiveJobs view:

Sample Query:

DELETE FROM ActiveJobs
WHERE JobID = 202;

Query Explanation: Any row that meets this condition is erased in the JobOpenings table. If your view combined records from more than one table, this command would typically fail or be disallowed.

Output:

(1 row affected)

4. The WITH CHECK OPTION Clause

Updatable views sometimes need further control so you do not enter data that falls outside their defined conditions. You can add WITH CHECK OPTION to enforce the same WHERE clause used in the view when inserting or updating.

Below is a snippet that illustrates how you might define a view with this clause:

Sample Code:

CREATE VIEW ActiveJobsSecure
AS
SELECT JobID, Title, Department
FROM JobOpenings
WHERE IsOpen = 1
WITH CHECK OPTION;

Query Explanation: The ActiveJobsSecure view allows you to view only job listings where IsOpen = 1. When you insert or update data through this view, the WITH CHECK OPTION makes sure you don’t accidentally add or change a job that isn’t active. It helps you maintain clean, reliable data by enforcing the filter condition.

Output:

Also Read: A Guide to Relationships in SQL: One-to-One, One-to-Many, and Many-to-Many

Now, let’s look at why the different types of views in SQL are beneficial.

Advantages and Disadvantages of SQL Views

SQL views offer flexibility, security, and improved query organization, but they can also introduce complexity and performance concerns if misused. The right view type depends on your data needs, whether for simplicity, speed, or controlled access. Knowing the trade-offs helps you design smarter data solutions.
Here’s a clear comparison of key advantages and disadvantages of using SQL views:

What Are the Best Practices for Working with Views?

Views can feel tricky at first, but once you get the hang of them, they become powerful tools for organizing, securing, and speeding up your data work. To get the most out of them, follow a few tried-and-true tips that boost clarity, performance, and control.

1. Use Clear Naming Conventions: Stick to meaningful names, like vw_EmployeeList instead of View1. A good prefix (like vw_) and a hint of purpose in the name go a long way in making your views readable and manageable.

CREATE VIEW vw_EmployeeDetails AS
SELECT EmployeeID, FirstName, LastName
FROM Employees
WHERE Status = 'Active';

2. Think Performance First: Don’t overload your view with extra columns or complex joins unless needed. Keep it lean and focused especially if it's used often.

CREATE VIEW vw_DepartmentSales AS
SELECT DepartmentID, SUM(TotalAmount) AS TotalSales
FROM Sales
WHERE SaleDate >= '2025-01-01'
GROUP BY DepartmentID;

3. Use Views for Security: Views let you control who sees what. Instead of giving table access, create views that hide sensitive information like salaries or personal data.

CREATE VIEW vw_PublicEmployeeData AS
SELECT EmployeeID, FirstName, Department
FROM Employees;
GRANT SELECT ON vw_PublicEmployeeData TO PublicUser;

4. Leverage Indexing Where Needed: If a view runs on large data and is read-heavy, go for an indexed materialized view. It makes repeated queries faster.

CREATE MATERIALIZED VIEW mv_IndexedSales AS
SELECT Region, ProductID, SUM(SalesAmount) AS TotalSales
FROM Sales
GROUP BY Region, ProductID;
CREATE INDEX idx_Sales ON mv_IndexedSales (Region, ProductID);

5. Avoid Deep Nesting: Chaining too many views makes them slow and messy. Combine logic into one or two layers to keep things fast and clean.

-- Instead of nesting:
CREATE VIEW vw_FilteredRegionSales AS
SELECT Region, TotalSales FROM vw_RegionSales WHERE TotalSales > 10000;

-- Just simplify:
CREATE VIEW vw_OptimizedRegionSales AS
SELECT Region, SUM(SalesAmount) AS TotalSales
FROM Sales
WHERE SalesAmount > 10000
GROUP BY Region;

Also Read: SQL Jobs for Freshers: Salary, Career Growth & Opportunities

Next, let’s look at how upGrad can help you learn SQL concepts.

How Can upGrad Help You Learn SQL?

To manage modern databases efficiently, it’s important to understand the different types of views in SQL, including simple, complex, materialized, and partitioned views. Each plays a role in streamlining queries, securing data,  or boosting performance. 

By using the right view for the task, like a simple view for quick filters or a materialized view for faster reporting, you can simplify data access. This helps you write cleaner, more efficient SQL code that’s easier to maintain. 

Along with the courses provided above, here are some additional courses that can help you in your learning journey:

• Introduction to Data Analysis using Excel
• Basics of Inferential Statistics
• Introduction to Tableau
• Case Study using Tableau, Python and SQL
• Data Structures & Algorithms

If you're unsure where to begin or which area to focus on, upGrad’s expert career counselors can guide you based on your goals. You can also visit a nearby upGrad offline center to explore course options, get hands-on experience, and speak directly with mentors!

Boost your career with our popular Software Engineering courses, offering hands-on training and expert guidance to turn you into a skilled software developer.

Explore our Popular Software Engineering Courses

Master in-demand Software Development skills like coding, system design, DevOps, and agile methodologies to excel in today’s competitive tech industry.

In-Demand Software Development Skills

Stay informed with our widely-read Software Development articles, covering everything from coding techniques to the latest advancements in software engineering.

Read our Popular Articles related to Software