Data Export MySQL Workbench: 2 Easy Methods

By: Published: June 17, 2020

data export mysql workbench

Often, there is a need to migrate data from MySQL to external sources, which may be to a file (CSV, Excel), another database, a cloud platform, or some other external tool. The movement of data is required when you want to perform analytics on the data (which may not be possible in MySQL itself) or to move the data into a modern ecosystem for better compatibility.

This article will give you a comprehensive guide on MySQL and its key features in brief. You will also explore various methods to export data from MySQL. The primary focus of this article is the Data Export MySQL Workbench feature which will also be discussed in further sections. By the end of this article, you will gain complete knowledge about these methods and their implementation.

Table of Contents

What is MySQL?

MySQL Logo
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MySQL is an accessible and popular open-source Relational Database. It is widely used by many small and big industries when there is a need to store structured data and perform quick analytics to understand the behavior of the data.

Key Features of MySQL

Some of the most important key features of MySQL are as follows:

  1. Free Source: Free and easy to use.
  2. ANSI SQL: MySQL uses the standard form known as ANSI SQL with a universe of Data Analytical functions.
  3. Driver availability: With the help of available drivers, it can easily integrate with many programming languages and modern tools.
  4. Integration: Easy integration with operating systems.
  5. Support huge databases: MySQL provides support for large databases, up to 50 million rows or more in a table. 
  6. Memory Usage: The default file size limit for a table is 4GB, but this can be increased to a limit of 8 million terabytes (TB) (provided the operating system supports it).

To know more about MySQL, visit this link.


You will have a much easier time understanding the ways for the Data Export MySQL Workbench feature if you have gone through the following aspects:

  1. MySQL Server running on-premise or on the cloud.
  2. Basic knowledge of Data Export MySQL Workbench feature.

Note: This article uses MySQL 8.0.20 to demonstrate the Data Export MySQL Workbench feature.

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Why exporting a database is important?

  • Back up for catastrophic system failure: Exporting a database creates a backup that you can use to restore your database in case of system failure.
  • Data versioning: Specific versions on your database can be saved by exporting the database from MySQL. You can analyze or restore any particular version of the database.

Methods to Export Data from MySQL

There are various ways by which you can export MySQL data, i.e., by using the in-house Data Export MySQL Workbench feature or programmatically (Python, Java, etc.) or by some other ways. Here you will look into the most popular and easy way to export the data from MySQL:

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Before we start discussing different methods to export data, let’s first consider the following points:

  1. The schema we have defined is “test”.
  2. The table name is “orders”.
  3. The orders contain the following attributes:
    1. order_id: Id of the order placed.
    2. order_date: Date of the order placed.
    3. custormer_id: Id of the customer who has placed the order.
  1. The MySQL Server’s process should have write access to the target folder containing the target CSV file.
  2. The target CSV file must not exist.

Method 1: Data Export MySQL Workbench Feature

The Data Export MySQL Workbench feature provides an inbuilt option to export the data into CSV format.

You can download Data Export MySQL Workbench from here. Below is the step-by-step procedure on how you can utilize the Data Export MySQL Workbench feature with ease.

  1. First, prepare the query and execute it to get the desired result set.
Querying for data export Mysql workbench
Image Source: Self
  1. From the result panel, click on the Export option.
Saving the Query data
Image Source: Self
  1. On the save dialog box, enter the file name, choose CSV as the file format, and click the Save button as shown by the image below.
Data Export Feature in MySQL Workbench
Image Source: Self

Method 2: Using MySQL Commands

The simple way to export data from MySQL is to use the inbuilt feature of extracting the data by using the SQL approach. This command exports the data into CSV format with the specified “delimiter” and “escape characters”. 

CSV files are the best when we talk about Data Analytics because of their structured format and ease of integration with the existing available tools.

Step 1: First, we have to prepare the query which contains the desired data to be exported. Here, we are exporting the data where order_status is COMPLETED.

Step 2: Mention the optional parameters like field delimiter, field enclosing option, and execute the query using execute option in the Workbench.

  1. Step 3: On successful completion of the query, the CSV will be exported to the mentioned location.

Below are the schematics for the MySQL command :

Data Export Commands in MySQL Workbench
Image Source: Self

Below is the command for your reference :

SELECT order_id, order_date, customer_id, order_status
FROM test.orders
WHERE order_status = 'COMPLETE' 
INTO OUTFILE 'c:/Temp/output/Completed/orders.csv' 


There are a variety of options in the market to migrate or export data from the MySQL server to the required destination. One of the popular in-house options among them is the Data Export MySQL Workbench feature which has been discussed in this article. Now, you have a comprehensive idea of how you can easily export data using the Data Export MySQL Workbench and SQL commands.

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Have you used the Data Export MySQL Workbench feature? Let us know in the comments section below.

Vishal Agrawal
Freelance Technical Content Writer, Hevo Data

Vishal has a passion towards the data realm and applies analytical thinking and a problem-solving approach to untangle the intricacies of data integration and analysis. He delivers in-depth researched content ideal for solving problems pertaining to modern data stack.

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