Preamble
Oracle/PLSQL LNNVL function is used in the WHERE SQL query sentence to evaluate the state when one of the operands may contain the value NULL.
Oracle/PLSQL syntax of LNNVL function
LNNVL( condition_id )
The LNNVL function will return to the following:
| The condition is assessed as | LNNVL will return the value |
| TRUE | FALSE |
| FALSE | TRUE |
| UNKNOWN | TRUE |
So, if we had two columns called qty and reorder_level, where qty = 20 and reorder_level IS NULL, the function LNNVL would return the following:
| Condition | The condition is assessed as | LNNVL will return the value |
| qty = reorder_level | UNKNOWN | TRUE |
| qty IS NULL | FALSE | TRUE |
| reorder_level IS NULL | TRUE | FALSE |
| qty = 20 | TRUE | FALSE |
| reorder_level = 20 | UNKNOWN | TRUE |
LNNVL function in the following versions of Oracle/PLSQL
Oracle 12c, Oracle 11g, Oracle 10g
The LNNVL function can be used in Oracle PLSQL.
Let’s have a look at an example. If we had a product table containing the following data:
| PROD_ID | QTY_ID | REORDER_LEVEL_ID |
| 1000 | 20 | NULL |
| 2000 | 15 | 8 |
| 3000 | 8 | 10 |
| 4000 | 12 | 6 |
| 5000 | 2 | 2 |
| 6000 | 4 | 5 |
And we wanted to find all the products whose QTY was below REORDER_LEVEL, let’s run the next SQL query:
SELECT *
FROM prods
WHERE QTY < REORDER_LEVEL;
The request will return the following result:
| PROD_ID | QTY_ID | REORDER_LEVEL_ID |
| 3000 | 8 | 10 |
| 6000 | 4 | 5 |
However, if we wanted to consider products that were lower than REORDER_LEVEL and REORDER_LEVEL had the value NULL, we would use the function LNNVL as follows:
SELECT *
FROM prods
WHERE LNNVL(QTY >= REORDER_LEVEL);
This will return the next result:
| PROD_ID | QTY_ID | REORDER_LEVEL_ID |
| 1000 | 20 | NULL |
| 3000 | 8 | 10 |
| 6000 | 4 | 5 |
In this example, the resulting set also contains prod_id 1000, which has REORDER_LEVEL NULL.
LNNVL FUNCTION IN 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
Why BFSI Leaders Are Turning to Enteros for Database Optimization, AI Ops, and Cloud FinOps Excellence
- 16 April 2026
- Database Performance Management
Introduction The Banking, Financial Services, and Insurance (BFSI) sector is undergoing a massive digital transformation. With the rise of digital banking, real-time payments, fraud detection systems, and AI-driven financial services, organizations are becoming increasingly dependent on high-performance data infrastructure. From managing millions of transactions per second to enabling real-time risk analysis and personalized customer experiences, … Continue reading “Why BFSI Leaders Are Turning to Enteros for Database Optimization, AI Ops, and Cloud FinOps Excellence”
How to Optimize Telecom Sector Growth with Enteros AIOps Platform, Resource Metadata, Hierarchy Metadata, Spot Instances, and RevOps Efficiency
Introduction The telecom sector is at the center of global digital transformation, enabling connectivity for billions of users, businesses, and emerging technologies like IoT, 5G, and edge computing. As demand for high-speed, reliable communication services continues to rise, telecom providers are under immense pressure to scale operations efficiently while maintaining performance and controlling costs. However, … Continue reading “How to Optimize Telecom Sector Growth with Enteros AIOps Platform, Resource Metadata, Hierarchy Metadata, Spot Instances, and RevOps Efficiency”
Who Should Adopt Enteros for Retail Growth Management with AI SQL and Cloud FinOps Efficiency
Introduction The retail sector is evolving at an unprecedented pace, driven by digital transformation, omnichannel experiences, and data-driven decision-making. From global eCommerce giants to mid-sized retail chains, businesses are increasingly relying on cloud infrastructure, databases, and analytics platforms to fuel growth. However, this rapid expansion introduces a fundamental challenge:how to scale efficiently while maintaining performance, … Continue reading “Who Should Adopt Enteros for Retail Growth Management with AI SQL and Cloud FinOps Efficiency”
How to Optimize Technology Sector Growth with Enteros Database Management Platform, Cloud FinOps, and RevOps Efficiency
Introduction The technology sector is at the forefront of innovation, powering digital transformation across industries. From SaaS platforms and cloud-native applications to AI-driven solutions, technology companies are scaling rapidly to meet growing global demand. However, this rapid expansion introduces a critical challenge:how to sustain growth while maintaining high-performance systems, controlling cloud costs, and aligning operations … Continue reading “How to Optimize Technology Sector Growth with Enteros Database Management Platform, Cloud FinOps, and RevOps Efficiency”