Are you looking to transfer your data from REST API to MySQL? Do you find integrating your MySQL database with REST API servers challenging? If yes, then you’ve landed at the right place! This article will discuss the two best methods to transfer your data from REST API to MySQL database.

After reading this blog, you should be able to successfully set up a REST API MySQL connection and seamlessly transfer your data for analysis. It will further help you build a customized MySQL REST API ETL pipeline for your organization.

So let’s get started!


The MySQL REST API is an interface that enables web-based applications to interact with a MySQL database using the principles of Representational State Transfer (REST). This API allows for the manipulation of data stored in a MySQL database, facilitating actions such as data extraction, modification, and retrieval through standardized HTTP requests like GET, PUT, POST, and DELETE. By adhering to REST principles, the MySQL REST API enhances performance, security, and flexibility, making it a valuable tool for developers working with MySQL databases in various projects.

How is MySQL API used in ETL?

Businesses often rely on data from multiple, siloed systems, making it critical to merge this information into a unified view for informed decision-making.

ETL (Extract, Transform, Load) is a key strategy for integrating data from various sources.MySQL plays a crucial role in an ETL pipeline:

  • Extract: The MySQL API can be used to extract data from business systems and load it into the database.
  • Transform: Before loading data into the target system, it must be cleansed, verified, sorted, and standardized. This transformation process helps ensure data quality and consistency.
  • Load: The transformed data is then loaded into the MySQL database, making it available for searching and analysis.

Using MySQL in an ETL pipeline offers several benefits:

  1. Single Point of View: Combining data from disparate systems provides a consolidated view, enabling more comprehensive analysis and visualization.
  2. Historical Context: An ETL pipeline can integrate information from legacy systems with newer data, allowing for historical comparisons and deeper insights.
  3. Efficiency and Productivity: Automating the ETL process through tools like streamlines data migration, reducing manual effort and the risk of errors.

Method 1: Using API-Based Custom Code Snippets to Load Data from REST API to MySQL

MySQL houses the support for numerous connectors and APIs (drivers) that allow users to establish a connection between different applications and MySQL database servers using various programming languages.

To use these drivers, you must install the driver using the binary distribution or build the driver from scratch. You can consider using tools like Maven if you plan to repeat this exercise for different data sources or destination MySQL servers.

You can learn more about how to connect REST API to database using these drivers and connectors and numerous concepts associated with it from the following sections:

  • Understanding the General Workflow of Loading Data from APIs
  • Understanding Connection Pooling
  • Understanding Multi-Host Connections
  • Understanding Data Compressions and Schema Validation
  • Understanding Logging

Understanding the General Workflow of Loading Data from APIs

To start loading data from REST APIs, you will first have to leverage the “DriverManager” class to obtain and establish a connection with your MySQL Server. You can use the following syntax for creating your connection URL:


There are multiple protocols that you can choose from to set up the connection with your MySQL servers. These are as follows:

  • jdbc:mysql: This protocol helps set up ordinary & JDBC failover connections.
  • jdbc:mysql:loadbalance: This protocol houses support for load balancing.
  • jdbc:mysql:replication: This protocol helps set up JDBC-based replication connections.

You can provide one or multiple hostnames in the “host parameter”, along with port numbers to specify host-specific properties. For example, you can create a connection URL as follows:


Once you’ve set up the necessary configurations, you need to create a statement object that will carry out SQL operations such as insert, delete, update, etc., and fetch results.

With your statement object ready, you will have to execute the insert command in a repetitive loop based on conditional logic. Once you’ve executed the insert statement or any other operation, you will need to close the statement and connection object.

For example, if you want to insert, set, and update values in your MySQL database using APIs, you can do so using the following lines of code:

While (someCondition) {
//LOAD the API driver 	
// Obtain a Connection 	   	        
	Connection conn = DriverManager.getConnection( "jdbc:mysql:replication//myUser:myPassword@[address=(host=myHost1)(port=1111)(key1=value1)] ");                          

//specify the INSERT statement 				 
	PreparedStatement stmt = conn.prepareStatement("INSERT into my_records" +" VALUES(?,?,?,?,?)");

// SET the values in your table columns 							
	stmt.setInt(1, 0);					
	stmt.setString(2, myString);					
	stmt.setString(4, myName);					
	stmt.setString(5, myRole);

//EXECUTE the update 					
	}// End of TRY block 
        catch (Exception e) {
        System.err.println("Error: ");

// CLOSE the Statement and Connection objects
	finally {
} // END of While loop 

This is how you can leverage in-built connectors and drivers to load data from REST API to MySQL.

Understanding Connection Pooling

Understanding Connection Pooling
Connection Pooling

MySQL allows users to manage data coming in from different sources at different speeds and across time intervals by setting up numerous connections using the connection pooling functionality, which helps boost the performance of your system and reduce overall resource consumption. You can automatically send new connections back to the pool with connection pooling.

You can configure the connection pool for your MySQL instance by accessing the application server configurations file using the Java Naming and Directory Interface (JNDI). Ensure that while defining the size for your connection pool, you keep track of the resources such as memory/CPUs/context switches etc., that you have in place.

Understanding Multi-Host Connections

Often in enterprise-grade databases and systems, you might have multiple MySQL instances that act as the destination-based receivers for your data. To manage a large set of connections constituting multiple hosts, ports, etc., you must leverage various operations such as replication, failover, load balancing, etc.

Understanding Data Compressions and Schema Validation

MySQL allows users to optimize network transmission and ingestion times by leveraging X DevAPI connections to compress data. To use such compression algorithms, you will have to negotiate with the server and fix the negotiation priority using the “xdevapi.compressionalgorithms” connection property.

It further allows users to manage the incoming data such as JSON documents using the schema validation functionality that validates each collection against a schema before inserting or updating any data. To do this, you can specify a JSON schema while creating or modifying a data collection. MySQL will then perform schema validation at the server level when you create or update the document.

It will even send an error, in case the data does not validate against the schema. 

Understanding Logging

MySQL Logs.

MySQL keeps track of all the database transactions such as data transfers, updations, deletions, etc., by maintaining a comprehensive log. It allows users to configure and manage the log maintenance by modifying/configuring the SLF4J and Log4J files.

Limitation of Using Customer Code Snippets and APIs to Load Data to MySQL

  • Using drivers requires keeping track of updates and manually updating them when new releases are available or when your technology stack(Java, Node.js, C++, Python) undergoes updates. Similarly, with new versions, existing API calls and methods may depreciate and require upgrades.
  • To ensure smooth data transfers and high efficiencies, you will have to add/remove/change the new properties associated with your connections when any change occurs.
  • Working with APIs to load data requires strong technical knowledge to handle operations such as connection pooling, query optimization, compression, validation, etc.

Method 2: Using Hevo Data, a No-code Data Pipeline

Hevo Data focuses on two simple steps to connect REST API to MySQL database.

Step 1: Configure your REST API Source

Connect Hevo Data with your REST API source by providing a unique name for your pipeline and information about the method you want to use, choosing between GET and POST. You will also need to provide the URL for your API endpoint, data root for your API, and your credentials such as username and password to allow Hevo to access your data, along with information about your query params and API headers.

Source Config
Configure REST API as Source

Step 2: Configure your MySQL Destination

Load data from REST API to MySQL by providing your MySQL database credentials, such as your authorized username, password, information about your host IP, and the port number value. You will also need to provide a name for your database and a unique name for this destination.

Destination Config
Configure MySQL as Destination

Hevo Data, a No-code Data Pipeline, helps you get data from API to MySQL and lets you visualize it in a BI tool. Hevo is the only real-time ELT No-code Data Pipeline platform that cost-effectively automates data pipelines that are flexible to your needs. With integration with 150+ Data Sources (40+ free sources), we help you not only export data from sources & load data to the destinations but also transform & enrich your data, & make it analysis-ready.

Hevo allows you to focus on key business needs and perform insightful analysis using various BI tools such as Power BI, Tableau, etc. 



This article teaches you how to connect API to MySQL database and provides in-depth knowledge about the concepts behind every step to help you understand and implement them efficiently.

Implementing custom code to load data can be challenging, especially for beginners. It requires you to keep track of updates and manually update new releases. You also need to make changes in properties when connections change. This is where Hevo Data steps in. You can replicate your data from REST API to MySQL in easy three steps.

Why would you want to spend your engineering team’s bandwidth on this? You definitely got to make use of that for other high-priority tasks.

Also, please tell us about your experience loading data from REST API to MySQL! Share your thoughts in the comments section below!

Senior Customer Experience Engineer

Veeresh specializes in JDBC, REST API, Linux, and Shell Scripting. He excels in resolving complex issues, conducting brainstorming sessions, and implementing Python transformations, contributing significantly to Hevo's success.

No-code Data Pipeline For MySQL