Synchronous Data Mesh for GraphQL Queries
Publication date: April 25, 2022 (Diagram history)
This architecture shows how to use an API composition pattern to build a modern, distributed, and decentralized data architecture. It enables clients to query data where it lives, without first transporting it to a data lake or data warehouse. It also allows domain-specific teams to own and serve data as a product.
Synchronous Data Mesh for GraphQL Queries
The following steps describe the architecture:
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Expose your domain's schema through an HTTPS API with Amazon AppSync, allowing users to dynamically query a domain's data with GraphQL syntax.
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Compose the returning query results with a combination of resolvers built with AWS Lambda functions.
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For data partially available in a data lake, retrieve the data by running SQL queries supported by Athena. Run the Athena jobs asynchronously with the athena-express
library. -
For data partially available in databases, retrieve the data either directly from Amazon AppSync, or by using Lambda functions as proxy resolvers to your databases.
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For data partially available in external sources, use Lambda resolvers to fetch the data by invoking remote HTTP APIs.
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To improve your API's performance, enable server-side caching on Amazon AppSync.
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Other parties using AWS can replicate this architecture in their domains, also allowing clients to query their APIs using GraphQL, and composing the results with internal and external resolvers.
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Parties that do not use AWS can also expose their domains with GraphQL APIs built with other technologies, providing a seamless experience to clients.
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To retrieve large datasets, clients can subscribe to AWS Data Exchange instead.
Further reading
For additional information, refer to the following resources:
Diagram history
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| Change | Description | Date |
|---|---|---|
Initial publication | Reference architecture diagram first published. | April 25, 2022 |
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