REST API to MySQL: 2 Easy Methods

on Data Integration • January 18th, 2021 • Write for Hevo

REST API to MySQL

Do you want to transfer your data from REST API to MySQL? Is it challenging to integrate your MySQL database with REST API servers? If yes, then you’ve landed at the right place!

This article will detail the two best methods to transfer your data from REST API to MySQL.

Upon a complete walkthrough of the blog, you can successfully set up a connection between REST API servers & MySQL and seamlessly transfer your data for a fruitful analysis.

It will further help you build a customized ETL pipeline for your organization.

So let’s get started!

Table of Contents

Method 1: Using Hevo Data, a No-code Data Pipeline

Hevo Logo.

Hevo Data, a No-code Data Pipeline, helps you transfer data from REST APIs to MySQL & lets you visualize it in a BI tool.

Hevo is fully-managed and completely automates not only loading data from 150+ Data Sources but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code.

Its fault-tolerant architecture ensures that the data is handled securely and consistently with zero data loss.

Get Started with HEVO for FREE!

It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination.

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

Steps to use Hevo Data

Hevo Data focuses on two simple steps to get you started:

  • Configure 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
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  • Integrate Data: 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
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All of the capabilities, None of the firefighting

Using manual scripts and custom code to move data into the warehouse is cumbersome. Frequent breakages, pipeline errors, and lack of data flow monitoring make scaling such a system a nightmare.

Hevo’s reliable data pipeline platform enables you to set up zero-code and zero-maintenance data pipelines that just work.

Reliability at Scale – With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency. 

Monitoring and Observability – Monitor pipeline health with intuitive dashboards that reveal every stat of pipeline and data flow. Bring real-time visibility into your ELT with Alerts and Activity Logs. 

Stay in Total Control – When automation isn’t enough, Hevo offers flexibility – data ingestion modes, ingestion, and load frequency, JSON parsing, destination workbench, custom schema management, and much more – for you to have total control.    

Auto-Schema Management – Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps source schema with destination warehouse, so you don’t face the pain of schema errors.

24×7 Customer Support – With Hevo, you get more than just a platform. You get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform. Moreover, you get 24×7 support even during the 14-day full-featured free trial.

Transparent Pricing – Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spend. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow. 

Get started with HEVO for FREE!

Method 2: 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 using these drivers and connectors to load data from REST API to MySQL and numerous concepts associated with it from the following sections:

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:

protocol//[hosts][/database][?properties] 

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:

jdbc:mysql:replication//myUser:myPassword@[address=(host=myHost1)(port=1111)(key1=value1)]

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) {
	try{     	
//LOAD the API driver 	
	Class.forName("com.mysql.jdbc.Driver").newInstance();	
// 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(3,myAddress);					
	stmt.setString(4, myName);					
	stmt.setString(5, myRole);

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

// CLOSE the Statement and Connection objects
	finally {
	stmt.close(); 					
	conn.close();     	
	}
} // 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

Connection Pools: REST API to MySQL.

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 the 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 optimise 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 optimisation, compression and validation, etc.

Conclusion

This article teaches you how to easily load data from REST API to MySQL 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 & this is where Hevo steps in. 

Scale your Data Integration effortlessly with Hevo’s Fault-Tolerant No Code Data Pipeline

1000+ data teams rely on Hevo’s Data Pipeline Platform to integrate data from over 150+ sources in a matter of minutes.

Billions of data events from sources as varied as SaaS apps, Databases, File Storage, and Streaming sources can be replicated in near real-time with Hevo’s fault-tolerant architecture.

Hevo puts complete control in the hands of data teams with intuitive dashboards for pipeline monitoring, auto-schema management, and custom ingestion/loading schedules. 

This, combined with transparent pricing and 24×7 support, makes Hevo the most preferred data pipeline software on review sites.

Take our 14-day free trial to experience a better way to manage data pipelines.

Get started with HEVO for FREE!

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

No-code Data Pipeline For MySQL