PostgreSQL Schema Basic Operations

Schema is just not a technical argot if you have a fair knowledge of relational databases. It is the building block of relational databases that have conquered the modern tech stack.

PostgreSQL is one of the most famous and reliable databases whose characteristics allow its users to preserve and arrange the items in the current database and manage them in logical groupings.

PostgreSQL has several features that set it apart from other databases. You hit the correct link if you’re searching for a guide to understand PostgreSQL schema.

This post will give you an overview of the PostgreSQL schema, basic operations on schema along with examples. 

What is PostgreSQL?

PostgreSQL, usually known as Postgres, is a central SQL database management system (DBMS). It is open-source, free for personal and commercial use, and has a long history that began in 1996, building on previous software from the 1980s.

This DBMS requires extremely little work to maintain because of its remarkable stability. Because it is open-source software, its source code is accessible under the PostgreSQL License. Anyone with the necessary knowledge may use, edit, and distribute PostgreSQL in any form. You can read more about PostgreSQL on their official website.

What is Schema in PostgreSQL?

In relational database management systems (RDBMS), the term “schema” refers to the entire logical or physical architecture of the database, i.e., the definition of all the tables, columns, views, and other objects that comprise the database.

In the domain of Postgresql, the term “schema” may be better understood as a “namespace.”

Now you might be considering what is meant by namespace? A namespace is a somewhat flexible method of organizing and identifying information by name.

The significant points to note about the PostgreSQL schema are as follows:

• A schema contains all other database objects such as tables, views, stored procedures, triggers, etc.
• Postgresql schemas cannot be layered in a hierarchical structure. 
• While a database may have several schemas, there is only one level; hence schema names must be unique inside a database.
• In addition, every database must have at least one Schema. 
• A default schema named “public” is produced whenever a new database is created. 

Why is Schema Important in PostgreSQL?

Schemas can be helpful for a variety of reasons, including:

• Schemas are often used to logically organize data in databases to make it easily accessible and seamless to maintain. 
• In PostgreSQL schema enables a multi-user environment that allows numerous users to access the same database without interference. 
• Schemas are vital when several users use the application and access the database in their way or when various apps utilize the same database.
• With PostgreSQL schema, as a developer, you can separate test table logic(Schema) from production level logic(Schema). 
• You can effortlessly restore data from a different schema. Thus, application-oriented schemas may be retrieved and backed up separately for recovery and time travel. 
• You can manage application updates when the application data is in a schema. As a result, a new application version can work on the table structure in a new schema, including a simple schema name change.
• You can segregate stable and unstable data backups in a distinct schema. As a result, unstable data might have multiple backup plans from non-volatile data.

PostgreSQL Schema Overview

Schemas, in addition to just grouping database items into logical categories, to make them more understandable, have the practical goal of minimizing name collision. One operational paradigm entails creating a schema for each database user in order to give some kind of isolation, a place where users may build their own tables and views without interfering with one other.
The above-mentioned statements can be understood in the image depicted below.

In the above image, although the database has various tables and views with the same names, the schemas are maintaining an isolated environment.

Create PostgreSQL Schema

In PostgreSQL, the SQL syntax for defining a schema is as follows:
Syntax:

CREATE SCHEMA schema_name;  
Or  
CREATE SCHEMA [IF NOT EXISTS] schema_name; 

Where,

• Create Schema is a database term used to create a new schema.
• Schema_name argument is used to specify the Schema’s name, which should be unique in the existing database.
•  [IF NOT EXISTS] is an additional argument that is only used to establish a new schema if it does not exist.

Example:

CREATE SCHEMA employee;

This command requires database creation access, and the newly formed schema “employee” will be owned by the person who invoked the command.
A more complicated invocation may include optional parts defining a different owner and DDL instructions that instantiate database objects inside the Schema, all in one command!

The general structure is as follows:

CREATE SCHEMA schemaname [ AUTHORIZATION username ] [ schema_element [ ..... ] ]

where,

• “username” signifies who will own the schema 
• “schema_element” represents one of certain DDL commands. 
• Superuser privileges are required to use the AUTHORIZATION option.

Access PostgreSQL Schema Objects

To create or access objects in a schema, use a qualified name that consists of the schema name separated by a dot:

Syntax: 

schema_name.table_name

For Example:

Assume you have a marketing schema with a customer table and a public schema with a customer table as well. When referring to the staff table, you must provide the following qualifier:

public.customer
Or 
marketing.customer

The public Schema

In the previous section, we established tables without providing any schema names. By default, those tables and new objects are added to the public Schema.

PostgreSQL produces a public schema for each new database. As a result, the following instructions are the same functional:

CREATE TABLE table_name;  
And  
CREATE TABLE public.table_name; 

Alter PostgreSQL Schema

Rename Schema to a new name

In the case of a typo, the owner of a schema may modify the name, providing the user also has created privileges for the database.

The syntax of Alter Schema Command is as follows:

ALTER SCHEMA old_name RENAME TO new_name;

where,

• ALTER SCHEMA is a keyword to alter a schema.
• old_name is the schema name that you want to rename.
• new_name is the new name of the schema you want to replace with the older one.

Example:

ALTER SCHEMA staff to employees;

The above command will rename the schema named staff to a new name i.e. employees.

Note: You must be the owner of the schema and have the CREATE privilege for the database to execute the above statement.

Alter Owner of Schema

The ALTER SCHEMA command also allows you to alter the owner of a schema.

Syntax:

ALTER SCHEMA schema_name 
OWNER TO { new_owner | CURRENT_USER | SESSION_USER};

where,

• schema_name is the name of the schema to which you wish to alter the owner.
• OWNER TO is a keyword followed by the new owner’s name.

Example:

ALTER SCHEMA staff 
OWNER TO kate;

The above example uses the ALTER SCHEMA statement to change the owner of the schema staff to from public to kate.

Drop PostgreSQL Schema

There is a drop command that is used to remove a schema from a database.
The syntax of Drop Schema Command is as follows:

DROP SCHEMA [ IF EXISTS ] name [, ...] [ CASCADE | RESTRICT ]

where,

• schema_name indicates the name of the schema to be removed following the DROP SCHEMA keywords.
• IF EXISTS keyword signifies the conditionally delete schema only if it exists. It is used to avoid throwing exceptions if the schema doesn’t exist.
• CASCADE keyword is used to recursively delete all the functions, objects, tables, and everything that relay on the schema. You can use the RESTRICT option to remove schema only when it is empty. The DROP SCHEMA by default uses the RESTRICT option.

Note: You must be the owner of the schema or a superuser to execute the DROP SCHEMA command.

Example:

DROP SCHEMA IF EXISTS sales;

The above example uses the DROP SCHEMA statement to remove the salesschema present in your database:

The DROP command will fail if the Schema has any objects. Thus they must be destroyed first, or you may use the CASCADE argument to delete a schema and all its contents recursively.

DROP SCHEMA schema_name CASCADE;

Example:

DROP SCHEMA sales CASCADE;

The above command will delete the sales schema and its objects.

How to Select a Schema in PostgreSQL

To select a schema in PostgreSQL, you can set the search path to the desired schema using the following SQL command:

SET search_path TO schema_name;

• Replace schema_name with the name of your schema.
• Once set, any query will reference objects from this schema unless explicitly specified otherwise.
• To reset to the default schema (public), use:

SET search_path TO public;

This approach ensures you can organize and query your data efficiently within the specified schema.

Differences Between PostgreSQL Schema and Database

Aspect	Schema	Database
Definition	A logical subset within a database to organize objects like tables and views.	A complete storage unit for schemas and data.
Scope	Exists within a single database.	Operates independently, containing multiple schemas.
Isolation	Objects in schemas share the same database resources.	Each database has its own separate resources.
Usage	Used to organize and group related objects.	Used to completely separate applications or projects.
Access Control	Permissions are set at the object level within the schema.	Permissions are managed at the database level.
Examples	Schemas: public, sales, hr.	Databases: company_db, analytics_db.

Conclusion

In this blog post, you have learned about PostgreSQL Schema as well as its importance. You also walk through different syntax and examples provided for different scenarios to understand the subject better. 

PostgreSQL is one of the popular RDBMS. Its user base and use cases are increasing over time. Having a clear understanding of its features and schema helps you as a developer. Don’t forget to drop your comments and suggestions in the comment section below.

Exploring the journey doesn’t stop here, you can also check out our article on Creating PostgreSQL Tables.

If you use PostgreSQL, copying data into a warehouse using ETL scripts can be time-consuming. And, the fact that organizations require significant funds to recruit data engineers to maintain those scripts only exaggerates the problem — indeed, there must be a better way!

Luckily, you can set up and start Data Replication from PostgreSQL to your favorite warehouse in a matter of minutes using Hevo’s No-code Data Pipeline.

Sign up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

Frequently Asked Questions