What Is GraphQL?

The Graph Query Language (GraphQL) is an open-source query language for APIs, serving as a robust alternative to traditional REST APIs, offering precise and flexible data retrieval capabilities. It is more flexible than a standard API and less complicated than SPARQL, while retaining some of the stronger points of both approaches. This capability makes GraphQL particularly well-suited for front-end development, offering ease of use, a self-documenting nature, and granular control over API responses.

Advantages over REST

GraphQL addresses several limitations inherent in traditional REST APIs, primarily related to data fetching efficiency and client control:

• Single Request Efficiency: Unlike REST, which requires loading of data from multiple URLs (leading to “over-fetching” or “under-fetching”), GraphQL APIs get all the data your application needs in a single request, significantly improving application speed, especially over slow networks, and conserving bandwidth.
• Client-Defined Data: With REST, the server dictates the structure and content of the data returned. GraphQL empowers the client to explicitly define the exact data requirements within the operation declaration, giving developers unprecedented control over the response content.

Comparisons with SPARQL

While both GraphQL and SPARQL are powerful languages for querying complex graph-like data, they serve distinct purposes and excel in different contexts:

• Purpose: SPARQL is designed for querying RDF databases and highly flexible, complex relational structures. GraphQL is a more generalized API query language often used as an interface over various data sources, simplifying client-server interactions.
• Flexibility vs. Simplicity: SPARQL offers profound flexibility and advanced graph navigation capabilities whereas GraphQL prioritizes simplicity and reduced verbosity, though it offers less built-in flexibility.
• Syntax & Execution: GraphQL queries use a simpler, JSON-like syntax and are typically executed over a REST API or a simple endpoint. SPARQL uses its own distinct syntax and protocol for querying RDF directly.

GraphQL operations

Introspection

One of the most significant features of GraphQL is its introspection system. This feature allows clients to query which queries are currently supported by the API and how the system expects those queries to be called. This capability is built into the GraphQL system, enabling automated documentation and powerful, user-friendly tooling around API capabilities.

Technically, each introspection operation is considered a query. GraphQL’s introspection capability is crucial and sets it apart from SPARQL, which has no built-in method to examine the data model.

While RDF data and SPARQL can work without ontologies, GraphQL is, essentially, strongly typed. All objects and literals need to have a specific type, which has static relationships with the rest of the data model. Introspection allows you to retrieve metadata about the way in which those relationships are formed.

GraphQL’s strong typing lets it handle multiple data types and structures. It supports scalar types, objects, enums, and lists, allowing for detailed data structuring and manipulation within queries. GraphQL’s type system makes it easier to formulate complex, hierarchical data relationships than traditional RESTful services.

Strong typing means that you have a reliable source of information that is easy to validate. It doesn’t permit easy switching of datatypes, but that’s usually not an issue with most data lakes.

Queries

• Correspond to the READ operation in CRUD (Create, Read, Update, Delete).
• Allow fetching of multiple objects and deeply nested data structures in a single query, reducing the need for multiple API calls
• Support advanced features like filtering (both at the root level and for specific fields), limits, offsets, fragments (extracting parts of your query in a “fragment” to avoid repetition), and aliasing (changing name).

For example, the query above specifies that three characters who have an eye color are fetched from the database. It further refines that the value of the eyeColor field needs to be returned if and only if the character happens to be blue-eyed.

• Queries execute “bottom-up”: fields are fetched first and the whole object is returned after all fields are fetched (from the innermost to the outermost). If a required field’s value is missing, the entire object containing that field might be removed from the result set.

Mutations

• Enable to INSERT, UPDATE, and DELETE data.
• Follow largely the same principles and syntax as queries.
• Just like queries, mutations must return the changed objects, ensuring clients receive immediate feedback on the operation’s outcome.
• Values are passed as attributes to the mutation.
• Unlike queries, mutations are executed sequentially to avoid deadlocks
• A single mutation can modify multiple objects. Due to strong typing, validation is easy to achieve and can be backed by SHACL and frontend checks

Subscriptions

• Provide real-time updates from the server to the client.
• Maintain a steady connection over an open WebSocket.
• Notify the client whenever changes occur in the data. Note that this is related to changes in the object as a whole — a change in field X, which you don’t necessarily return as output from the subscription, would cause a new notification. In structure, subscriptions function exactly the same as queries.

Real-world applications and challenges

GraphQL has been widely adopted by many organizations seeking to improve their applications’ responsiveness and data interaction capabilities. GraphQL excels in environments requiring robust federation support and where parallelizing queries is beneficial.

GraphQL schemas can be “stitched” or “extended” to present a holistic, opaque view of the entire data model to the end-user. They don’t have to be familiar with the different constituent parts of the data and can have a singular unified access to it. This is made easier by the introspection system that keeps a unified schema constantly up to date.

Of course, GraphQL is not without challenges. The query parallelism capability and complexity, coupled with the lack of native graph traversal can lead to the “N+1 problem”. In it, the server makes multiple nested calls to databases. If each level obtains a nested object, which, in turn, obtains its own nested objects, a seemingly simple query can explode exponentially, only for the whole result to be nulled at a late stage due to a missing required field.

GraphQL and your applications

GraphQL stands out as a transformative technology in the realm of API design and data querying. With its robust, flexible capabilities and strong typing system, it offers an appealing solution for developers looking to build efficient, scalable applications.

As the technology matures, it is expected to solve more complex data retrieval needs, making it a staple in modern web development. By understanding these fundamentals, developers can better harness the power of GraphQL to enhance their applications and user experiences.