What is a knowledge graph API?

A knowledge graph API is a programming interface that allows developers to interact with a knowledge graph—a structured database that represents information as interconnected entities and their relationships. It provides methods to query, update, and manage data stored in the graph format, where nodes represent entities (e.g., people, places, concepts) and edges define the relationships between them (e.g., “works at,” “located in”). For example, a knowledge graph might store data like “Marie Curie → discovered → Radium,” linking entities through semantic relationships. APIs for knowledge graphs enable applications to retrieve specific subsets of this data or add new connections without needing direct access to the underlying database.

Developers typically interact with a knowledge graph API using HTTP requests to predefined endpoints. For instance, a query might ask for all entities related to a specific concept, such as “scientists who worked on radioactivity,” and the API would return structured data (often in JSON or XML) listing relevant entities and their connections. Some APIs support specialized query languages like SPARQL (used with RDF-based graphs) or GraphQL (for flexible data fetching). For example, Wikidata’s API allows SPARQL queries to fetch data like “list all Nobel Prize winners in Physics,” leveraging its vast network of interconnected facts. APIs may also include authentication, rate limiting, and pagination to manage data access efficiently.

Practical use cases for knowledge graph APIs include building recommendation systems, enhancing search functionality, or integrating disparate data sources. For example, an e-commerce app might use a product knowledge graph API to suggest related items based on shared attributes or user behavior. In enterprise settings, such APIs help unify data from siloed systems—like combining customer records with sales data—to create a holistic view. Tools like Google’s Knowledge Graph API or Amazon Neptune’s graph database service provide ready-to-use solutions, while open-source frameworks like Apache Jena allow developers to build custom APIs. By abstracting the complexity of graph queries, these APIs simplify working with interconnected data, enabling faster development of applications that rely on semantic relationships.