Updated March 6, 2023
Difference Between OData vs GraphQL
OData stands for Open Data Protocol, is an OASIS standard for REST API, which defines the best practices for building and consuming them. Microsoft developed it in 2007, which allows the creating and querying of interoperable Restful APIs in a simple way. It allows the programmer to focus on the business logic without worrying about the approaches to define other things like request/ response headers, status code, status code, media types, etc. It provides the rich query language with the features of sorting, filtering, querying, etc. It is strictly RESTful and expects and is URI- centric supporting the REST operations like GET, POST, PUT, DELETE, etc. In this topic, we are going to learn about OData vs GraphQL.
GraphQL is a query language for APIs used for fulfilling the queries with the existing data. Facebook developed it in 2015 before public release in 2015. It provides the complete description of data in your API with powerful data tools. It allows the single URI mapped to a web service with the API, which is capable of handling the most complex data requirements. It is not RESTful but provides many libraries for implementing and querying GraphQL. A single endpoint works great in GraphQL which makes it very easy to work for the consuming developer. It supports all the things related to the query, be it joins, selects, versioning, relationships, etc., in a single request/ response round trip.
Head to Head Comparison Between OData vs GraphQL (Infographics)
Below are the top differences between OData and GraphQL
Key Differences between OData and GraphQL
Below given are the key differences between the OData and GraphQL:
- OData is RESTFul, which means that it uses the REST pattern like POST, PUT, GET, DELETE to perform the desired operations, whereas GraphQL is not RESTful, which uses the Http with the POST request only in which the query is passed as body content.
- OData uses the URL to build the query, which sometimes hampers the size of the request, whereas, in the case of GraphQL, the query has its own definition as it is passed in the body is no issue regarding its size.
- OData is comparatively easy to understand and work for the programmers as the programmers are quite familiar with the REST-based frameworks. In terms of learning, GraphQL is a bit complex to understand for querying and implementing.
- OData supports the Delta Feeds, which is a standard way for providing the client specific link without being stateful, whereas GraphQL supports the Subscriptions, which is almost similar to the Delta Feeds in the GraphQL.
- In terms of coupling, OData provides the power of SQL to the URI at the cost of high coupling, whereas GraphQL behaves like a backend which brings all the Rest APIs all together in one interface.
- GraphQL provides a single endpoint to handle all the API requests, and there is no need to maintain the versioning endpoint. It also has an introspection endpoint which makes it easy to see the published schema and makes it easy to find tools. So, in this case, GraphQL is considered to be the best option.
- OData supports joins and relations in the form of relationships, but it does not support the versioning, unlike GraphQL, which supports the versioning, joins, selects, etc., from request/ response round trip.
- One positive point with the OData is that it provides a simpler definition for queries with easy and out of the box integration to migrate with the already existing webAPIs whereas in the case of GraphQL user has to do a lot of work like creating the schema, query, creating types for each query.
Comparison table between OData and GraphQL
Below given is the comparison table showing the head to head comparison between the OData and GraphQL:
| S.no. | OData | GraphQL |
| 1. | OData is basically a standard that defines the best practices for the user for building and consuming the restAPIs. | GraphQL is like a programming language, a query language that is used to fulfill those queries with the complete understanding of data in your API. |
| 2. | OData supports Delta Feeds, which is one of the standards and documented ways of calling the client links and is called to provide new entries in the array. | GraphQL supports Subscriptions which is almost similar to the Delta Feeds in OData but somehow more powerful than it. |
| 3. | It is comparatively easy to use for the programmers as only the REST knowledge is required to work with OData. | To work with GraphQL, developers need the two things, URI and the knowledge that API follows the standards of GraphQL. |
| 4. | In terms of scaling, one OData scheme would be hard to maintain and build for the whole organization. | One single data graph would be easy to create and maintain for the whole organization. |
| 5. | OData is a big name and open standard which is used by big companies that use SAP, .NET, etc. | GraphQL has comparatively broader adoption by big companies. |
| 6. | Though OData provides an attractive and simpler concept to deal with the data produced by the API, it is comparatively less powerful than GraphQL. | GraphQL is a self-contained and powerful query language, including all the things for querying and implementing the Rest API. So it is more powerful in comparison to OData. |
| 7. | GraphQL is a self-contained and powerful query language, including all the things for querying and implementing the Rest API. So it is more powerful in comparison to OData. | GraphQL supports joins relationships, sorting, versioning, pagination from a single request/ response round trip. |
| 8. | OData works best when the developers come from different technology backgrounds to consume the API as it provides a simpler concept for the queries to meet the required use cases. | GraphQL is comparatively harder to implement and is not RESTful. But it has the power to attract the desired tribe as it provides a lot of facilities. |
Conclusion
The above description clearly explains what OData and GraphQL are and the major difference between the two. GraphQL is comparatively expensive and harder to understand, and moreover, it is not RESTful, unlike OData, but it has a higher learning curve than OData. As both are widely used these days by programmers. It totally depends on the choice of the programmer and the requirement of the project to implement them according to the specific requirements.
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