Difference between View and table in SQL

sql

data-management

database-design

performance-optimization

byAlex Kataev·Dec 9, 2024

At its core, a View is a "ghost table" — a virtual table produced by a query on existing tables. On the other hand, a Table is a "storage unit" — a physical structure that holds actual data.

In a snapshot:

Persistence: Tables store data; Views pull data on-demand.
Mutability: Tables are editable; Views are typically read-only, though some updates are possible.
Speed: Tables provide immediate data access, while Views require query processing each time.
Access control: Views serve as data filters, hiding complexities or sensitive data.

-- Table: Just plain old employee data, nothing fancy here
CREATE TABLE employees (
    id INT,
    name VARCHAR(50),
    dept_id INT
);

-- View: Taking a sneak peek at IT folks without prying too much
CREATE VIEW it_dept_names AS
SELECT name
FROM employees
WHERE dept_id = 10;

Use Tables as your SQL data palette and Views as your creative brush for specific insights.

Interpreting Views and Tables

Security and Abstraction with Views

Views let you present data without modifying the table schema. They serve as abstraction layers converting complex queries into reusable bits. This disconnect between data representation and storage optimizes multi-tiered application architectures.

Views also handle security: You can exhibit a subset of columns, concealing sensitive information. This ability makes Views useful for creating a controlled data scene tailored to different user roles.

Performance Pros and Cons

Performance-wise, Views can be both a blessing and a curse. Although they reduce complex query redundancy, Views can introduce overhead by recalculating data each time. Yet, Indexed Views offer an adequate compromise — they store a result set enabling faster retrieval but demand more storage.

Versatility and Logical Design

Views are vital for conceptual design, offering a logical arrangement representative of business operations or user interfaces. When your data model evolves, modifying a View is generally less disruptive than changing underlying tables, ensuring data management flexibility.

Views: How and When

Views are particularly advantageous when you:

Need to distill complex data structures.
Require limited access to sensitive columns.
Seek a stable data interface for apps, despite table changes.

Views: Potential Pitfalls

However, keep these Views constraints in mind:

Dependency: Modifications to base tables can break Views.
Extra overhead: Particularly with complex Views or non-indexed ones.
Write operation limits: Some Views do not support INSERT, UPDATE, or DELETE actions.

Advanced Views Trivia

Indexing: A Performance Hack

Indexed Views improve read performance by pre-storing the result set, behaving similar to physical tables. They perform best when underlying data has minimal changes.

Data Manipulation with Views

Use Instead of Triggers with Views to support write operations. This approach enables complex CRUD operations while encapsulating business rules and maintaining data integrity.

Views in DSL (Data Specific Language)

In conceptual database design, Views are your domain-specific language, formalizing business rules and relations, acting as a logical blueprint. They reduce application code complexity by encapsulating it within the database.

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