Materialized View orTemporary Tables in SQL

In typical SQL world (Structured Query Language), usually managing and manipulating data efficiently is very crucial for its performance, database lifecycle or DWH scalability. Temporary tables and materialized views are two powerful constructs (objects) that help in achieving both objectives simultaneously. Even though each serves a unique purpose within data operations and data streams. Let´s look at both little closer.

Temporary Tables

We can define them as typical tables which are created within a database session and are only available during the lifetime of that particular session. Lifetime during session is critical as they are designed to store intermediate results, results of window functions for complex calculations or data processing tasks and massive data manipulations.

Temporary tables are essentially useful in scenarios where data needs to be temporarily held and manipulated without affecting the main database tables. Here comes why it is called “temporary”. After your session ends, the temporary table is automatically discarded - same as you run command DROP TABLE, after query results are taken into another step. This way processing ensures no permanent database storage is consumed. You can imagine storing all 245 steps and their output tables consisting of 6 billion rows and 700 columns each day to have versions of each step.

There are characteristics which are distinguishing types of tables:

• Session-specific: Visible and accessible only within the session they were created.
• Volatile: Automatically deleted at the end of the database session.

Common use cases are Session-specific as analysts and developers do not usually implement critical changes to core database on daily basis. Both types of temporary tables improve query performance by reducing the need for repeated calculations or data retrieval operations.

Materialized Views

A very typical materialized view is a database object that contains the results of a query. Unlike a standard view, which is a virtual table that dynamically retrieves data from the underlying tables, a materialized view stores the query result as a physical table that can be refreshed periodically or on demand. Materialized views are used to optimize performance, especially for complex queries over large datasets where execution times can be significant. They are ideal for reporting and analytics, where the same aggregate data is accessed frequently.

Characteristics and differentiators vs Temporary Tables:

Unlike temporary tables, materialized views are stored in the database until explicitly dropped. Command is necessary to be run to terminate their existence. They can be configured to refresh on a schedule or on a manual basis, ensuring data is up to date as needed. Materialized views are also significantly improving performance for read-heavy operations by precomputing and storing the query result.

Typical Projects and Use Cases

Materialized views are used to pre-aggregate data for fast access by reporting and analytics tools, while temporary tables might be used during the ETL (Extract, Transform, Load) process for intermediate data manipulation. A typical use case is legendary Data Warehousing.

Next on the road where Temporary tables bring many calms and sleepful nights to developers are Web Applications. Temporary tables can be used for session-specific data processing, such as personalizing content for a user, while materialized views might store frequently accessed data, such as top-rated products.

Financial Analysis: In financial systems, materialized views can help in quickly accessing complex financial metrics and reports, whereas temporary tables could be used for transactional analysis and processing within a user's session.

Last but least is to mention and finish the section that most modern relational database management systems (RDBMS) like PostgreSQL, MySQL, Oracle Snowflake and SQL Server support temporary tables and materialized views, each with their specific syntax and feature sets.