Preamble
In this post you will learn how to get the number of MySQL lines in a database.
Getting the number of MySQL rows in one table
To get the number of rows per table, you use the COUNT(*) operator in SELECT as follows:
SELECT
COUNT(*)
FROM
table_name;
For example, to get the number of rows in the andreyex table in a database example, use the following operator:
SELECT
COUNT(*)
FROM
andrex;
+ ---------- +
| COUNT(*) |
+ ---------- +
| 35 |
+ ---------- +
1 row in set (0.01 sec)
Getting the number of MySQL rows in two or more tables
To get the number of rows in several tables, you use the UNION operator to combine sets of results returned by each individual SELECT operator.
For example, to get the number of rows in a table and the number of rows in a single query, use the following instructions.
SELECT
'andrex' tablename,
COUNT(*) rows
FROM
andrex
UNION
SELECT
"trainings" tablename,
COUNT(*) rows
FROM
I'm sorry;
| tablename | rows |
| andrex | 34 |
| | 451 |
2 rows in set (0.01 sec)
Getting the number of MySQL rows of all tables in a particular database
To get the number of rows of all tables in a particular database, such as classicmodels, you use the following steps:
- First, get all table names in the database
- Second, create a SQL statement that includes all SELECT COUNT(*) FROM table_name operators for all tables separated by UNION.
- Third, execute a SQL statement using the prepared statement
First, to get all the names of the database tables, you query the following from the information_schema database:
SELECT
table_name
FROM
information_schema.tables
WHERE
table_schema = 'classicmodels'
AND table_type = 'BASE TABLE';
+ -------------- +
| TABLE_NAME |
+ -------------- +
| andrex |
|
| sites |
+ -------------- +
3 rows in set (0.02 sec)
Second, to build the SQL operator, we use GROUP_CONCAT and CONCAT functions as follows:
SELECT
CONCAT(GROUP_CONCAT(CONCAT('SELECT ''',
table_name,
'' table_name,COUNT(*) rows FROM ',
table_name)
' UNION '),
' ORDER BY table_name')
INTO @sql
FROM
table_list;
This query contains a list of table_list table names, which is the result of the query at the first stage.
The next query uses the first query as a derived table and returns the SQL instruction as a string.
SELECT
CONCAT(GROUP_CONCAT(CONCAT('SELECT ''',
table_name,
'' table_name,COUNT(*) rows FROM ',
table_name)
' UNION '),
' ORDER BY table_name')
INTO @sql
FROM
(SELECT
table_name
FROM
information_schema.tables
WHERE
table_schema = 'classicmodels'
AND table_type = 'BASE TABLE') table_list
If you use MySQL 8.0+, you can use MySQL CTE (generic table expression) instead of a derived table:
WITH table_list AS (
SELECT
table_name
FROM information_schema.tables
WHERE table_schema = 'classicmodels' AND
table_type = 'BASE TABLE'
)
SELECT CONCAT(
GROUP_CONCAT(CONCAT("SELECT '",table_name," table_name,COUNT(*) rows FROM ",table_name) SEPARATOR " UNION "),
' ORDER BY table_name'.
)
INTO @sql
FROM table_list;
Third, you execute the @sql operator using the prepared operator as follows:
PREPARE s FROM @sql;
EXECUTE s;
DEALLOCATE PREPARE s;
Getting the number of MySQL rows of all tables in a database by one query
A quick way to get the number of rows of all tables in the database is to query data from the information_schema database directly:
SELECT
table_name,
table_rows
FROM
information_schema.tables
WHERE
table_schema = 'classicmodels'
ORDER BY table_name;
This method is sometimes not accurate because the number of rows in information_schema and the actual number of rows in tables are not synchronized. To avoid this, you must follow the ANALYZE TABLE instruction before requesting the number of rows in the information_schema database.
ANALYZE TABLE table_name,...;
In this article you learned about different ways to get the number of rows of one or more tables in a MySQL database.
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
How AI-Driven FinOps and AIOps Improve Performance Across Banking Cloud Environments
- 25 August 2026
- Database Performance Management
Introduction The banking industry is rapidly transitioning from traditional infrastructure models toward cloud-native, hybrid, and multi-cloud environments. Digital banking applications, payment platforms, lending systems, customer portals, fraud detection platforms, and financial analytics increasingly depend on cloud infrastructure to deliver scalable and reliable services. This transformation provides banks with greater flexibility, but it also introduces a … Continue reading “How AI-Driven FinOps and AIOps Improve Performance Across Banking Cloud Environments”
How to Optimize Telecom Database Infrastructure with Enteros Database Software, AIOps, and Cloud FinOps
Introduction Telecommunications companies operate some of the most complex technology environments in the world. Subscriber management, billing, charging, network inventory, service provisioning, CRM, usage analytics, 5G, IoT, edge computing, and digital customer platforms all generate massive database workloads. As telecom operators expand 5G, cloud-native architectures, edge computing, and AI, the amount and complexity of data … Continue reading “How to Optimize Telecom Database Infrastructure with Enteros Database Software, AIOps, and Cloud FinOps”
Building Resilient BFSI Applications with Predictive AIOps and FinOps Intelligence
- 23 August 2026
- Database Performance Management
Introduction The Banking, Financial Services, and Insurance (BFSI) industry is undergoing a rapid digital transformation. Mobile banking, digital payments, online lending, insurance platforms, wealth management applications, and real-time financial services now depend on highly available and scalable IT infrastructure. Customers expect BFSI applications to be fast, secure, and available around the clock. Even a short … Continue reading “Building Resilient BFSI Applications with Predictive AIOps and FinOps Intelligence”
How AIOps and FinOps Enable Smarter Cloud Cost Optimization in Banking
Introduction Banking has entered an era where cloud technology is central to digital transformation. Mobile banking applications, digital payments, online lending, fraud detection, open banking APIs, wealth management platforms, and real-time financial services all depend on highly available and scalable IT infrastructure. Cloud adoption gives banks the flexibility to scale resources as demand changes, but … Continue reading “How AIOps and FinOps Enable Smarter Cloud Cost Optimization in Banking”