All About Materialized Views in SQL Server

In SQL Server, a materialized view is a database object that contains the results of a precomputed query. Unlike a regular view, which simply defines a SQL query that is executed each time it is queried, a materialized view stores the results of the query in a physical table-like structure. This can provide significant performance benefits for queries that involve large amounts of data or complex calculations.

Materialized Views VS Database View

With the usual syntax of creating a view, we create a database view and that's different from the materialized view because usual database view is just a virtual table that is defined by a SQL query. It is stored in the user database and can be accessed by users who have the appropriate permissions. A view does not store any data itself; it is simply a way of presenting data from one or more tables in a different way.

Here are some key characteristics of database views:

• The view is stored in the user database, not the tempdb database.

• The view definition is persistent, but the data is not stored in the view itself.

• A view can be used to simplify queries by presenting data from one or more tables in a more readable or meaningful way.

• Views can be used to enforce security by limiting the columns or rows that users can access.

• Views can be used to simplify application development by providing a consistent way of accessing data.

Coming back to the materialized views

When a materialized view is created, the results of the associated query are computed and stored in a table in the database. This table is updated periodically based on a schedule or triggered by certain events, such as changes to the underlying data. Queries that reference the materialized view can then retrieve the pre-computed results directly from the table, rather than executing the original query each time.

Materialized views can be particularly useful for data warehousing and business intelligence applications, where complex queries are often run against large data sets. By pre-computing the results of these queries and storing them in a materialized view, query response times can be significantly improved.

Example code to create a materialized view in SQL server

CREATE MATERIALIZED VIEW sales_by_region
AS
SELECT region, SUM(sales_amount) AS total_sales
FROM sales_table
GROUP BY region

Once the materialized view is created, you can query it just like a normal table:

SELECT * FROM sales_by_region

This will return the precomputed query results stored in the materialized view.

In Azure SQL Server, as in "Materialized Views" are NOT supported natively, here this structure can be accessed using Indexed Views or Azure Synapse Analytics materialized views

To create an indexed view, we can use the CREATE VIEW statement with the WITH SCHEMABINDING option to bind the view to the schema of the underlying table(s). This ensures that any changes to the table schema are propagated to the view.

CREATE VIEW sales_by_region WITH SCHEMABINDING
AS
SELECT region, SUM(sales_amount) AS total_sales
FROM sales_table
GROUP BY region

CREATE UNIQUE CLUSTERED INDEX IX_sales_by_region
ON sales_by_region (region)

After defining the query like materialized view example above, we can also create a unique clustered index on the view to optimize query performance. The index should be created on the column(s) that are commonly used in query predicates or joins, which in this case is the region column.

Cons of Materialized Views

• Requires additional disk space as query results are to be stored on disk

• Will not be useful and might even affect the performance negatively if the view is set for frequent updates

• Not every SQL Server edition supports Materialized Views. So it's important to check the specific edition and version being used before attempting to create one.

❓How are materialized views different from normal tables in SQL server?

Materialized views and normal tables serve different purposes and have different performance characteristics. Materialized views are useful for precomputing the results of complex queries and storing them in a physical table-like structure for fast query response times, while normal tables are used to store and manage large amounts of data and complex data structures that can be modified using SQL statements.

The main differences could be segregated into the following categories.

1. Query Results Storage:

   A normal table stores data, while a materialized view stores the results of a precomputed query.

2. Data Persistence:

   Normal tables are persistent database objects that remain in the database until they are explicitly dropped, while materialized views are refreshed periodically or triggered by certain events and contain precomputed query results that may be outdated until the next refresh.

3. Query Performance:

   Normal tables are persistent database objects that remain in the database until they are explicitly dropped, while materialized views are refreshed periodically or triggered by certain events and contain precomputed query results that may be outdated until the next refresh.

4. Data Modification:

   Normal tables can be modified using INSERT, UPDATE, and DELETE statements, while materialized views are read-only and cannot be directly modified.

5. Size and Complexity:

   Normal tables can store large amounts of data and complex data structures, while materialized views are typically used to store simplified, precomputed query results that are optimized for query performance.

❓How are Materialized views different from temporary tables?

Materialized views and temporary tables are two different database objects that serve different purposes. Materialized views are useful for precomputing the results of complex queries and storing them in a physical table-like structure for fast query response times, while temporary tables are useful for the temporary storage of query results within a single session or stored procedure.

Here are some key differences between them.

1. Query Results Storage:

   A materialized view stores the results of a precomputed query in a physical table-like structure, while a temporary table stores the results of a query in a temporary table structure that is dropped automatically at the end of the session or stored procedure.

2. Query Recomputation:

   A materialized view is recomputed periodically based on a schedule or certain events, such as changes to the underlying data, while a temporary table is recomputed each time the query is executed.

3. Query Performance:

   Materialized views can provide significant performance benefits for queries that involve large amounts of data or complex calculations because the query results are precomputed and stored in the table structure. Temporary tables can also improve query performance in some scenarios, but may not be as efficient as materialized views for complex queries or large data sets.

4. Data Persistence:

   Materialized views are a persistent object that remains in the database until it is explicitly dropped, while temporary tables are temporary object that is dropped automatically when the session or stored procedure ends.