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GraphQL Voyager vs Serverless AppSync: What are the differences?
Data source handling: In GraphQL Voyager, data sources need to be manually connected and defined using the schema. On the other hand, Serverless AppSync simplifies this process by providing built-in data source integration with various data storage options like DynamoDB, Elasticsearch, etc.
Real-time functionality: GraphQL Voyager is mainly focused on visualizing the GraphQL schema and relationships between types, whereas Serverless AppSync supports real-time functionality through its integration with AWS AppSync subscriptions, allowing for live data updates and notifications.
Authentication and authorization: Serverless AppSync provides built-in authorization and authentication mechanisms that can be easily configured within the service, including options for API key, IAM, and Cognito authentication. In contrast, GraphQL Voyager does not offer such built-in functionality for managing access control.
Custom resolvers: Serverless AppSync allows developers to create custom resolvers to manipulate data fetched from different data sources, enabling more complex data operations. GraphQL Voyager, on the other hand, does not provide this capability as it is primarily focused on schema visualization.
Schema stitching: Serverless AppSync supports schema stitching, which allows combining multiple GraphQL schemas into a single schema, enabling developers to create unified APIs from various sources. This feature is not available in GraphQL Voyager, which is more geared towards exploring individual schemas.
Deployment and scalability: Serverless AppSync is a fully managed service by AWS, which handles deployment, scaling, and availability of the GraphQL API. In contrast, deploying and managing GraphQL Voyager requires more manual effort and setup, making it less scalable for production environments.
In Summary, GraphQL Voyager is a tool for visualizing GraphQL APIs, while Serverless AppSync is a managed GraphQL service with real-time functionality, authentication features, custom resolvers, schema stitching, and scalability advantages.