DATA TYPES
POSTGRESQL

A Comprehensive Guide to Data Types in Postgres

intro

This blog post will inform readers about the several data types in Postgres, which are the different types of data that can be stored in a Postgres database while using a tool like DbVisualizer to manage these data types.

Tools used in the tutorial
Tool Description Link
Dbvisualizer DBVISUALIZER
TOP RATED DATABASE MANAGEMENT TOOL AND SQL CLIENT
PostgreSQL logo POSTGRESQL
THE POSTGRESQL DATABASE

This blog post will inform readers about the several data types in Postgres, which are the different types of data that can be stored in a Postgres database while using a tool like DbVisualizer to manage these data types.

Preface

Data types in PostgreSQL define the type of data that can be stored in a table column and help ensure the accuracy and efficiency of data storage and retrieval. Postgres offers a wide range of data types, each coming with its specific characteristics.

PostgreSQL is also unique in that it has 43 data types, more than any other database management system available on the market - with each of these data types serving a unique purpose, storing data doesn’t get much fancier than that.

This article will demonstrate the process of connecting to a Postgres database using DbVisualizer, creating tables, and inserting data with its appropriate data type into the tables. This will give readers an edge in comprehending data types in a Postgres database and how to manage them efficiently using DbVisualizer.

Understanding PostgreSQL data types

In computing, data types are categories that specify the kind of data that a variable or an expression can hold. Data types define the format, range, and operations that can be performed on data. They tell the type of data that can be stored in the column of a table and determine the correct interpretation and manipulation of the data. As already mentioned above, Postgres offers a wide range of data types. Let us look at some of the data types in Postgres:

Character data types in PostgreSQL

Character data types are used to store text data. Postgres offers three different character data types: character varying (varchar), text, and character.

  • Character varying (varchar): Varchar is used to store variable-length character strings. The maximum length of a varchar string is specified when the table is created.
  • Text: Text is used to store variable-length character strings of any length.
  • Character: Character is used to store fixed-length character strings. The length of a character string is specified when the table is created.

Numeric data types in PostgreSQL

Numeric data types are used to store numerical data. Postgres offers four different numeric data types: integers, floating-point numbers, fixed-point numbers, and booleans.

  • Integers: Integers are used to store whole numbers. Postgres offers three different integer data types: Smallint, Integer, and Bigint. These differ in their storage size and value range.
  • Floating-point numbers: Floating-point numbers are used to store numbers with fractional parts. Postgres offers two different floating-point data types: Real and Double precision. Real numbers are less precise but require less storage space than double precision numbers.
  • Fixed-point numbers: Fixed-point numbers are used to store numbers with a fixed number of decimal places. Postgres offers a single fixed-point data type: Numeric.
  • Booleans: Booleans are used to store true or false values.

Date and time data types in PostgreSQL

Date and time data types are used to store date and time values. Postgres offers four different date and time data types: date, time, timestamp, and time with time zone (timestamptz).

  • Date: Date is used to store the date without the time.
  • Time: Time is used to store the time without the date.
  • Timestamp: Timestamp is used to store the date and time together.
  • Time with time zone (timestamptz): Timestamptz is used to store the date and time together with the time zone.

Other data types in PostgreSQL

Postgres also offers some other data types, including arrays, geometric data types, JSON and JSONB data types, range types, and network address data types.

  • Arrays: Arrays can be used to store a list of values of the same data type.

    Geometric data types: Geometric data types can be used to store geometric shapes, such as points, circles, boxes, and polygons.

  • JSON and JSONB: JSON and JSONB are used to store JSON data. JSONB is a more efficient way to store JSON data than JSON, but it does not support all of the features of JSON.

  • Range: Range types can be used to store a range of values, such as a range of dates or a range of numbers.

  • Network addresses: Network address data types can be used to store network addresses, such as IP addresses and MAC addresses.

The Significance of PostgreSQL Data Types

PostgreSQL data types are important for several reasons. They ensure that data is stored and subsequently processed successfully. Specifying the type of data that can be stored in a column also helps prevent common programming mistakes, enables efficient memory location by determining the appropriate amount of space required for different types of data, and enhances the readability of code by making it clear what kind of data is being handled and how it should be interpreted.

How to Select the Correct PostgreSQL Data Type

When choosing data types, there are some factors to consider: the data type, the size of the data, the performance requirements, the portability needs, etc.

  • Type of data: The first step is to identify the type of data that will be stored.
  • Size of the data: The size of the data is also important to consider. For example, if you need to store a small number of whole numbers, then the smallint data type may be sufficient. However, if you need to store a large number of whole numbers, then you may need to use the bigint data type.
  • Performance requirements: Some data types are more efficient than others for certain operations. For example, the integer data type is more efficient for arithmetic operations than the floating-point data type.
  • Portability needs: If you need to be able to port your database to a different database system, then you should choose data types that are supported by most database systems.
  • Potential future use of the data: If you think that you may need to use the data for a different purpose in the future, then you should choose a data type that is flexible enough to accommodate that data.

When taken into careful consideration, these factors help utilize memory space and improve the performance of database applications.

How to use PostgreSQL data types

As a sequel to the factors to consider when selecting a data type, let us also keep these in mind:

  • Integers: Use integers for whole numbers, such as customer IDs, product IDs, and order IDs.
  • Floating-point numbers: Use floating-point numbers for numbers with fractional parts, such as product prices and shipping costs.
  • Fixed-point numbers: Use fixed-point numbers for numbers with a fixed number of decimal places, such as currency values and interest rates.
  • Booleans: Use booleans for true/false values, such as whether a customer is subscribed to a mailing list.
  • Character varying (varchar): Use varchar for variable-length character strings, such as customer names and product descriptions.
  • Text: Use text for variable-length character strings of any length, such as blog posts and user comments.
  • Character: Use character for fixed-length character strings, such as postal codes and license plate numbers.
  • Date: Use date for date values, such as order dates and customer birth dates.
  • Time: Use time for time values, such as business hours and shipping times.
  • Timestamp: Use timestamp for date and time values together, such as event times and login times.
  • Time with time zone (timestamptz): Use timestamptz for date and time values together with the time zone, such as flight departure times and customer support hours.
  • Arrays: Use arrays to store a list of values of the same data type.
  • Geometric data types: Use geometric data types to store geometric shapes.
  • JSON and JSONB: Use JSON and JSONB to store JSON data.
  • Range types: Use range types to store a range of values.
  • Network address data types: Use network address data types to store network addresses.

PostgreSQL data types in a database client like DbVisualizer

DbVisualizer can help Postgres users manage and query data types by providing information about data types, allowing the conversion of data type and validation, and also, querying data by data type and also providing a user-friendly interface for managing and querying data in the database. To be able to visualize the integration of DbVisualizer with Postgres, we will have to follow a few steps:

Step 1: Connecting To The Database Server

Firstly, we'll need to employ DbVisualizer to establish a connection to our database server. In today’s lesson, we’ll be using the Postgres database server. We can establish a connection to a database server in DbVisualizer by creating a new database connection from the "Create Database Connection" menu, selecting a driver for your database, entering the connection details such as the name, database type, server IP, port, user account, and password and clicking "Connect" to access the database as shown in the image below:

Connected to a Postgres Database
Connected to a Postgres Database

Step 2: Working with Postgres Using DbVisualizer

Now we will create a table with multiple data types, insert data into it, and visualize everything with DbVisualizer.

Creating a Table and Adding Columns

Click on the plus icon to open the SQL commander.

Opening the SQL Commander in DbVisualizer.
Opening the SQL Commander in DbVisualizer.

Let us build a SQL query in which a “transactions” table will be created with multiple columns.

  • “transactionId” should have an INTEGER data type and should be set as the primary key, meaning it is a unique identifier for each row in the table.
  • “item” should be a VARCHAR(50) data type and should be set to NOT NULL, meaning it cannot have a NULL value.
  • “description” should have a VARCHAR(2000)data type - let it have a NULL value too.
  • Create a “date” column with a date data type and set it to NOT NULL, meaning it cannot have a NULL value.
  • “quantity” with an INTEGER data type set to NOT NULL, meaning it cannot have a NULL value.
SQL Query Creating a ‘transactions’ Table.
SQL Query Creating a ‘transactions’ Table.
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1 CREATE TABLE transactions ( 2 transactionId INTEGER PRIMARY KEY, 3 item VARCHAR(50) NOT NULL, 4 description VARCHAR(2000) NULL, 5 date DATE NOT NULL, 6 quantity INTEGER NOT NULL 7 );

Now, let us verify that the transactions table has been created by navigating postgres>Schemas>public>Tables and right-clicking to refresh the objects tree as shown below:

The Public Schema Annotation.
The Public Schema Annotation.

We can see that the table has been created successfully.

The Created ‘transactions’ table
The Created ‘transactions’ table

Inserting Data into Table Columns

Let us execute the following query to insert data into the ‘transactions’ table columns:

SQL Query Inserting Values into the ‘transactions’ Table.
SQL Query Inserting Values into the ‘transactions’ Table.
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1 INSERT INTO transactions (transactionId, item, description, date, quantity) 2 VALUES (1, 'Rice', 'A bag of rice', '2023-11-09', 10), 3 (2, 'Juice', 'Orange juice', '2023-11-10', 5), 4 (3, 'Beer', 'Scottish Whiskey', '2023-11-11', 18);

Data has been successfully inserted into the “transactions” table.

Successfully Inserted Data into the ‘transactions’ Table.
Successfully Inserted Data into the ‘transactions’ Table.

Conclusion

In conclusion, selecting the appropriate data types for each column is important in database management as it ensures that data is stored and subsequently processed successfully. We also learned that defining the type of data that can be stored in a column enables efficient memory location by determining the appropriate amount of space required for different types of data.

DbVisualizer’s user-friendly interface allows for easy connections to several databases including Postgres databases. It allows the creation of tables with different datatypes within its SQL Commander, insertion and retrieval of data, etc. By utilizing DbVisualizer, DBAs can effectively manage their Postgres databases and can help them ensure the accuracy and efficiency of data storage and retrieval.

To learn more about database management, make sure to keep an eye on our DevTalk forum, and until next time.

FAQs

What are the different PostgreSQL data types?

Postgres supports a wide variety of data types, including numeric, character, boolean, date and time, interval, etc.

What are some of the common data type errors in PostgreSQL?

Some of the common data type errors in PostgreSQL include:

  • Using the wrong data type for the column which leads to inaccurate data processing and performance issues
  • Not specifying a default value for the column which also leads to NULL values in the column making it difficult to query and manipulate the data.

How do I convert a column from one data type to another in PostgreSQL?

To convert a column from one data type to another in Postgresql, you can use the ALTER TABLE statement. For example, to convert the transactionId column from an integer to a numeric data type, you would use the following statement:

Successful Change of the Data Type to ‘Numeric’
Successful Change of the Data Type to ‘Numeric’

What are the three types of Character data types in PostgreSQL?

The three types of character data types in PostgreSQL are the character varying (varchar), text, and character.

How do I select the correct PostgreSQL data type?

To select the correct PostgreSQL data type, know the type of data, the size of the data, and the performance requirements of the database application, etc. These factors come together to improve the performance of the database application.

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About the author
Leslie S. Gyamfi.
Leslie S. Gyamfi
Leslie Gyamfi is a mobile/web app developer with a passion for creating innovative solutions. He is dedicated to delivering high-quality products and technical articles. You can connect with him on LinkedIn
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