Preamble
In this tutorial you will learn how to use Oracle ALIASES (aliases for columns or tables) with syntax and examples.
Oracle ALIASES can be used to create an alias for a column or table.
ALIASES columns are used to simplify the reading of columns in your resulting set.
ALIASES tables are used to shorten your SQL code to make it easier to read or when you make a standalone connection (i.e.: enumerating the same table more than once in the FROM sentence).
Syntax for ALIAS columns in Oracle / PLSQL
column_name AS alias_name
OR
Syntax for ALIAS tables in Oracle / PLSQL
table_name alias_name
Parameters or arguments
- column_name – the original name of the column to which you want to specify an alias.
- table_name – the initial name of the table to which you want to specify an alias.
- alias_name – the nickname for the destination.
Note: If alias_name contains spaces, you must quote alias_name.
Example of ALIAS as a column
Typically, aliases are used to simplify the reading of column headers in your resulting set. For example, when fields are concatenated, you may get the following result.
For example:
SELECT contact_id, first_name || last_name AS NAME
FROM contacts
WHERE last_name = 'Anderson';
In this example, we replaced the second column (that is: first_name and last_name concatenated) as NAME. The result is that the NAME will appear as the header for the second column when the resulting set is returned.
Since our alias_name contains no spaces, we do not have to wrap alias_name in quotes.
However, it would be acceptable to write this example using quotes as follows:
SELECT contact_id, first_name || last_name AS "NAME"
FROM contacts
WHERE last_name = 'Anderson';
Then let’s take a look at an example where we should quote alias_name.
For instance:
SELECT contact_id, first_name || last_name AS "CONTACT NAME"
FROM contacts
WHERE last_name = 'Anderson';
In this example, we changed the second column (i.e.: first_name and last_name were concatenated) to “CONTACT NAME”. Since there are spaces in this alias, “CONTACT NAME” must be enclosed in quotes.
Example ALIAS table
When you create an alias for a table, this is either because you plan to list the same table name more than once in the FROM sentence (i.e.: join), or you want to shorten the table name to make the SQL statement shorter and easier to read.
Let’s take the example of ALIAS table name in Oracle / PLSQL.
For example:
SELECT p.product_id, p.product_name, categories.category_name
FROM products p
INNER JOIN categories
ON p.category_id = categories.category_id
ORDER BY p.product_name ASC, categories.category_name ASC;
In this example, we created an alias for the products p. table. In this SQL instruction, we can now refer to the products table as p.
When creating table aliases, there is no need to create aliases for all tables listed in the FROM sentence. You can create aliases for any or all tables.
For example, we could change our example above and create an alias for the table in this way.
SELECT p.product_id, p.product_name, c.category_name
FROM products p
INNER JOIN categories c
ON p.category_id = c.category_id
ORDER BY p.product_name ASC, c.category_name ASC;
We now have an alias for the categories c table, and an alias for the products p table.
What are Table Aliases? (Introduction to Oracle SQL)
About Enteros
Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of clouds, RDBMS, NoSQL, and machine learning database platforms.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
Keeping Operations Running at Scale: Enteros’ AIOps-Driven Database Performance Platform
- 27 January 2026
- Database Performance Management
Introduction In manufacturing plants and insurance enterprises alike, operational continuity is non-negotiable. A delayed production schedule, a failed claims transaction, or a slow underwriting system can ripple into lost revenue, regulatory exposure, and eroded customer trust. At the heart of these operations sit databases—quietly powering everything from shop-floor automation and supply chain planning to policy … Continue reading “Keeping Operations Running at Scale: Enteros’ AIOps-Driven Database Performance Platform”
Managing Real Estate Data at Scale: Enteros AI Platform for Database Performance and Cost Estimation
Introduction The real estate sector has undergone a dramatic digital transformation over the past decade. From commercial real estate (CRE) platforms and property management systems to residential marketplaces, smart buildings, and PropTech startups, modern real estate enterprises are now fundamentally data-driven organizations. Behind digital leasing platforms, pricing engines, tenant experience apps, IoT-enabled buildings, analytics dashboards, … Continue reading “Managing Real Estate Data at Scale: Enteros AI Platform for Database Performance and Cost Estimation”
Governing AI Performance in Technology Enterprises: Enteros GenAI-Driven Intelligence Platform
- 26 January 2026
- Database Performance Management
Introduction Artificial Intelligence has moved from experimentation to the core of modern technology enterprises. AI now powers customer experiences, revenue optimization, fraud detection, personalization engines, autonomous operations, developer productivity tools, and mission-critical decision systems. From SaaS platforms and digital marketplaces to enterprise software and AI-native startups, organizations are embedding AI into nearly every layer of … Continue reading “Governing AI Performance in Technology Enterprises: Enteros GenAI-Driven Intelligence Platform”
Optimizing Healthcare Databases at Scale: How Enteros Aligns GenAI, Performance Intelligence, and Cloud FinOps
Introduction Healthcare organizations are under unprecedented pressure to deliver better patient outcomes while operating within increasingly constrained financial and regulatory environments. Hospitals, payer networks, life sciences companies, and digital health platforms now rely on massive volumes of data—electronic health records (EHRs), imaging repositories, genomics pipelines, AI-driven diagnostics, claims systems, and real-time patient monitoring platforms. At … Continue reading “Optimizing Healthcare Databases at Scale: How Enteros Aligns GenAI, Performance Intelligence, and Cloud FinOps”