Range Types
Range types offer a concise way to represent a range of values within a single database field. They find application in various domains, from temporal data to numeric intervals. In this blog article, we'll be delving into their usage (and benefits!) using both DML/SQL statements and Navicat for PostgreSQL 16.
Arrays and Enums
PostgreSQL, renowned for its extensibility and versatility, offers several data types beyond the conventional integer and string. Among these are the array and enum, which empower developers with advanced data modeling capabilities. In this blog article, we'll be delving into these sophisticated data types, demonstrating their usage and benefits within the context of the free dvdrental sample database.
In the dynamic landscape of database management systems, selecting the right platform for your project is a crucial decision. With an array of options available, each catering to specific needs, making a choice can be a daunting task. This blog will outline a few reasons why PostgreSQL may just be the relational database solution you're looking for.
Last week's tutorial guided us through the creation of Materialized Views in PostgreSQL, using the DVD Rental Database as a practical example. As we learned there, PostgreSQL Materialized Views provide a powerful mechanism to enhance query performance by precomputing and storing the result set of a query as a physical table. Today's follow-up will cover other pertinent Materialized View operations such as refreshing a view, executing queries against it, as well as deleting a view should you no longer require it. As with the last blog article, we'll go over both DML statements as well as how to achieve the same result via the Navicat GUI.
PostgreSQL Materialized Views provide a powerful mechanism to enhance query performance by precomputing and storing the result set of a query as a physical table. This tutorial will guide you through the creation of Materialized Views in PostgreSQL, using the DVD Rental Database as a practical example.
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