DB2 Materialized Query Tables vs Views Note from the Data Whisperer
By Tom Nonmacher
In the world of SQL databases, using views and materialized query tables (MQTs) can drastically improve the efficiency of your data operations. Today, we will be exploring the differences between DB2 Materialized Query Tables (MQTs) and views, and how each can be used to optimize your database performance. This discussion will primarily focus on IBM's DB2 11.5, but we'll also touch on SQL Server 2019, MySQL 8.0, Azure SQL, and Azure Synapse.
A view in SQL is essentially a virtual table based on the result-set of an SQL statement. It contains rows and columns, just like a real table, and the fields in a view are fields from one or more real tables in the database. Views do not hold any data themselves; they pull data from the underlying tables when queried. Here is a simple example of creating a view in DB2:
-- DB2 code for creating a view
CREATE VIEW view_name AS
SELECT column1, column2,...
FROM table_name
WHERE condition;
On the other hand, an MQT is a table that materializes the results of a query, hence the name. Unlike a view, which only stores the SQL statement, an MQT actually stores the result set of the query. This can drastically improve performance for complex queries or queries that are run frequently, as the database can simply retrieve the pre-computed results from the MQT, rather than executing the query again. Here's an example of creating an MQT in DB2:
-- DB2 code for creating an MQT
CREATE TABLE mqt_name AS (
SELECT column1, column2,...
FROM table_name
WHERE condition)
DATA INITIALLY DEFERRED REFRESH DEFERRED;
It's important to note that while both views and MQTs can help optimize your database performance, there are some key differences between them. As we've discussed, an MQT stores the result set of a query, which can significantly speed up query execution times. However, because it stores this data, it also consumes storage space. A view, on the other hand, does not consume any storage space, because it only stores the SQL statement and retrieves the data from the underlying tables in real time.
The choice between using views or MQTs will depend on your specific use case. If you're dealing with complex queries or queries that are run frequently, and you have sufficient storage space, using an MQT can significantly improve your database performance. On the other hand, if storage space is a concern, or if your data is updated frequently, a view could be a better choice.
In conclusion, both views and Materialized Query Tables have their advantages and can be used to optimize database performance in different situations. Understanding the differences between them can help you make more informed decisions about how to structure and manage your database. Regardless of the platform you are using, be it DB2, SQL Server, MySQL, Azure SQL, or Azure Synapse, these principles hold true and can be implemented to enhance your database operations.