
DbSchema | SQLite - How to Create Views?
Table of Contents
- Introduction
- Prerequisites
- What is a View?
- Usage of Views
- Advantages and Limitations of Using a View
- Creating a View in sqlite3
- Creating a View in DbSchema
- Conclusion
- References
Introduction
SQLite
is a C-library that provides a disk-based database with zero configuration and no server process requirement. This article explores a key feature of SQLite and other SQL databases — the View. We’ll discuss the concept of views, their uses, advantages, and limitations. Additionally, we’ll provide a detailed guide on creating views in sqlite3 and DbSchema.
Prerequisites
Basic knowledge of SQL is essential to understanding this article. Familiarity with SQLite and the basics of the sqlite3 command-line utility and DbSchema would be helpful.
For installation and establishing connection you can read our article SQLite-How to create a database?
What is a View?
In SQL, a View is a virtual table based on the result-set of an SQL statement. It contains rows and columns, just like a real table. The fields in a view are fields from one or more real tables in the database. A view does not physically exist. It is a set of queries that, when invoked, provide a tabular result similar to a regular database table. However, views don’t store data — they pull from other tables.
Usage of Views
Complexity Hiding: Views can hide the complexity of data. A view can encapsulate complicated joins, aggregations, and calculations into a simpler table.
Data Protection: Views can limit the degree to which the underlying database schema is exposed. They can also provide a level of abstraction over your tables, providing a measure of security.
Data Preparation: They can transform the data into a format that application-specific code can work with.
Advantages and Limitations of Using a View
Advantages:
Data security: Views restrict user access to the data because the view can display selective columns from the table.
Complex queries can be encapsulated in a view for repeated usage.
Data from multiple tables can be combined and represented as one entity.
Limitations:
When a table is dropped, associated views become irrelevant.
You can’t create a view on temporary tables or associated indexes.
In SQLite, you can’t use the DROP VIEW IF EXISTS statement.
Creating a View in sqlite3
Here’s how to create a view using sqlite3:
Step 1: Create and connect to your database:
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To know more about creating a database you can read our article SQLite-How to create a database?
Step 2: Create a sample table:
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To know more about creating a table you can read our article SQLite-How to create a Table?
Step 3: Insert some sample data:
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Sample Database
Employees table:
ID | Name | _Role_ |
---|---|---|
1 | John Doe | Manager |
2 | Jane Smith | Developer |
3 | David Gray | Developer |
4 | Mia Brown | Sales |
5 | Max Green | Developer |
Step 4: Create a view
Here we create a view that shows all developers:
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Step 5: Use the view:
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Result After Executing the Query:
After executing a query on the Developers view, the result would be:
_Name_ |
---|
Jane Smith |
David Gray |
Max Green |
This output table shows that we have three Developers in our company according to the Employees table: Jane Smith, David Gray, and Max Green.
Creating a View in DbSchema
DbSchema
is a visual database designer that allows managing SQL and NoSQL databases using interactive diagrams.
Step 1: Launch DbSchema and connect to your SQLite database.
Step 2: Right-click on the canvas and select Create View.
Step 3: Enter the SQL statement to define your view.
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Step 4: Click Apply to create the view.
You can now use the view like any other table in your database.
Visually Manage SQLite using DbSchema
DbSchema is a SQLite client and visual designer. DbSchema has a free Community Edition, which can be downloaded here.
Key Features of DbSchema:
Following are the key features of DbSchema which distinguish it from other database GUI tools.
Conclusion
Views
in SQLite and other SQL databases provide a powerful tool for abstracting the underlying schema, improving data security, and simplifying complex queries. While they come with certain limitations, their benefits far outweigh these in most use cases.