Different Software Systems can behave better when combined. But how can two different Software Systems unify forces to communicate and exchange data in a coherent way? A number of standards and protocols have been discovered to facilitate communication between different systems. If you have ever explored these systems, you might have come across two popular technologies: OData and REST APIs. 

These two are technologies used to facilitate communication and interaction between different Software Systems. Although the two are closely related, they are not the same. There are major and significant differences between the two technologies. In this OData vs REST APIs article, we will help you to know everything about these two technologies. We will answer questions like, “What is OData?” and “What is REST?”. We will then go deeper and discuss the differences between OData and REST.

Table of Contents

Understanding the Concept of REST APIs

Image Source: Astera Software

REST (REpresentational State Transfer) refers to a Software Architectural Style that defines the standards for exchanging information between two different systems via the HTTP Protocol. It is the most popular architecture for exchanging data on the World Wide Web.

REST defines 6 different principles for Web Services:

  • Uniform Interface: All components in a REST system must adhere to the same interface and rules so as to communicate with each other. 
  • Client-Server: REST separates Servers from Clients. The Servers store information, while the Clients retrieve information from the Servers. 
  • Stateless: All requests made via REST are stateless. They have all the necessary information needed by the Server to execute the request. 
  • Cacheable: In REST, both Clients and Servers can cache resources, which is good for reducing traffic and improving performance. 
  • Layered System: REST supports a Layered System Architecture. The Client may communicate with one Server, while the other Servers perform tasks such as Data Storage and Authentication. 
  • Code on Demand: REST requisitions may return executable code or logic when necessary (optional). 

Any API (Application Programming Interface) that follows the above principles is referred to as a REST API. In most cases, REST APIs use XML or JSON, but the REST Architecture doesn’t require anything specific as far as this is concerned. REST does not require any particular format, but it accepts any format that can be used in Content Negotiation

Understanding the Concept of OData

OData (Open Data Protocol) is a set of best practices for developing and using RESTful APIs. It helps you to focus on your Business Logic while creating RESTful APIs without the need to worry about various ways to define request and response Headers, HTTP Methods, Status Codes, Media Types, URL Conventions, Payload Formats, and more. 

OData Architecture: OData vs REST
Image Source: Progress Software

OData carries the following specifications:

  1. It must follow REST principles unless there is a clear reason why it should not.
  2. The OData services MUST have support for Atom encoding.
  3. OData services SHOULD have support for JSON encoding. 

REST is the most essential component technology of OData. OData 3.0 standards require OData users to follow REST principles. OData rests on HTML technology, which resolves the problem of being REST-based in a way. It supports two Protocols for Data Transfer, the XML-based Atom format and JSON. 

OData also has guidance for performing actions like defining reusable procedures, tracking changes, and sending many REST requests.  

It provides two models for Data Management which include:

  1. Entity Data Model (EDM): This is an abstract Data Model that OData users MUST use to describe the exposed data. 
  2. Service Model: It is made up of Static Resources and a set of Dynamic Resources. The work of the Static Resources is to provide a way of asking the Service about its Data Model, while the Dynamic Resources provide methods to manage the Data Model.

In the next section, we will be discussing OData vs REST APIs to know how the two compare in different core areas. 

Simplify REST API ETL with Hevo’s No-code Data Pipeline

A fully managed No-code Data Pipeline Platform like Hevo Data helps you integrate and load data from 100+ Data Sources (Including 40+ Free Data Sources) to a destination of your choice in real-time in an effortless manner. Hevo further provides a Native REST API Connector for free to help you load data from Custom and Non-native Data Sources to your desired destination without writing a single line of code.

Get Started with Hevo for Free

Hevo with its minimal learning curve can be set up in just a few minutes allowing the users to load data without having to compromise performance. Its strong integration with umpteenth sources allows users to bring in data of different kinds in a smooth fashion without having to code a single line. 

Check out some of the cool features of Hevo:

  • Completely Automated: The Hevo platform can be set up in just a few minutes and requires minimal maintenance.
  • Connectors: Hevo supports 100+ Integrations to SaaS Platforms, Files, Databases, and BI Tools. It supports various destinations including Amazon Redshift, Google BigQuery, Snowflake and Firebolt Data Warehouses; Amazon S3 Data Lakes; and MySQL, SQL Server, TokuDB, DynamoDB, PostgreSQL databases to name a few.  
  • Real-Time Data Transfer: Hevo provides Real-time Data Migration, so you can have analysis-ready data always.
  • 100% Complete & Accurate Data Transfer: Hevo’s robust infrastructure ensures reliable data transfer with zero data loss.
  • Scalable Infrastructure: Hevo has in-built integrations for 100+ sources that can help you scale your data infrastructure as required.
  • 24/7 Live Support: The Hevo team is available round the clock to extend exceptional support to you through Chat, Email, and Support Calls.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
  • Live Monitoring: Hevo allows you to monitor the data flow so you can check where your data is at a particular point in time.
Sign up here for a 14-Day Free Trial!

OData vs REST APIs: What’s the Difference?

Let’s now discuss how OData and REST APIs compare to each other:

OData vs REST APIs: Function

REST Function

REST is an architecture that defines how to send messages between a Client and a Server via HTTP. It is a model that states that you can use HTTP and its verbs to perform CRUD Operations (Create, Read, Update, Delete) on the resources exposed by your Services. Thus, REST is more concerned about the architecture. 

OData Function

OData is a standard from Microsoft that relies on the REST Architecture to send specific types of messages over HTTP. It defines metadata in CSDL (Common Schema Definition Language) format to describe the Entity types supported by your Service and their Properties, Data types, and more. Thus, OData is more concerned about the content.

OData vs REST APIs: Principles

REST Principles

REST defines 6 principles, as has been listed above, to ensure the creation of efficient Web Services and REST APIs must follow these principles. These principles ensure the success of REST Projects. 

OData Principles

OData is built on top of the REST Framework, thus, it depends on REST principles. Note that even though OData recommends its users to follow REST principles every time, the requirement can be relaxed in the case of a good reason. A very basic, Compliant Service should be easy to build, with additional work necessary only to support additional capabilities. 

OData vs REST APIs: Best Use Case

REST API Best Use Case

REST is used when there is a need to interact with a Data Source, for example, to retrieve data for all Products. It is easier and faster to parse data using REST APIs. It uses URI to expose the Business Logic. 

The following operations are available on HTTP:

URL Design and HTTP Method: OData vs REST
Image Source: Medium

OData Best Use Case

OData is best used to expose Services and APIs to Systems and Applications. It has facilities for extension to achieve the custom needs of the REST APIs. 

OData vs REST APIs: Data Transfer Format

REST Data Transfer Format

Data transfer format is an important factor to consider when comparing OData vs REST. REST supports the transfer of data in any format. Although most REST APIs use XML and JSON formats, REST is not specific in regard to this. 

OData Data Transfer Format

OData API specifies that the data should be transferred in either JSON, XML, or Atom format. 

Those were the major differences between OData vs REST.  


This blog discussed fine differences across OData vs REST APIs. We also discussed concepts behind OData and REST APIs, their specifications and principles. 

For Businesses, extracting complex data from a diverse set of Data Sources such as REST APIs can be a challenging task. This is where Hevo saves the day by providing an efficient, reliable and fast ETL Service.

Visit our Website to Explore Hevo

Hevo Data offers a faster way to move data from 100+ Data Sources such as REST API for free, into your Data Warehouse to be visualized in a BI tool. Hevo is fully automated and hence does not require you to code. Hevo provides a pre-built Native REST API Connector that will allow you to integrate data from a plethora of Custom and Non-native Sources. All this without writing a single line of code and free of cost.

Want to take Hevo for a spin? Sign Up here for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.

Share your learning experience using OData vs. REST APIs and the contrasts you found most useful. Let us know what you think in the comments area below!

Nicholas Samuel
Freelance Technical Content Writer, Hevo Data

Skilled in freelance writing within the data industry, Nicholas is passionate about unraveling the complexities of data integration and data analysis through informative content for those delving deeper into these subjects. He has written more than 150+ blogs on databases, processes, and tutorials that help data practitioners solve their day-to-day problems.

No-code Data Pipeline for Your Data Warehouse

Get Started with Hevo