Query AWS HealthLake data stores using SQL in Amazon Athena
Note
After February 20, 2023, HealthLake data stores do not use integrated natural language processing (NLP) by default. If you are interested in turning on this feature on your data store, see How do I turn on HealthLake's integrated natural language processing feature? in the Troubleshooting chapter.
When you create a HealthLake data store the highly nested FHIR data structure is ingested into Amazon Athena, and automatically transformed into Iceberg tables queryable with SQL. Granting access to this new resource is managed using AWS Lake Formation. Each FHIR resource type is represented as an individual table in Athena.
Important
For data stores created before November, 14, 2022, you must migrate your existing data store to a new one to query it using SQL. For help, see Migrating an existing data store to use Amazon Athena.
To create a HealthLake data store, you must add additional IAM policies and a service role to your IAM user or role that is a HealthLake administrator. For more information about setting up permissions, see Setting up permissions to start using AWS HealthLake.
HealthLake data stores are ingested into Athena as Iceberg tables. To learn more about how Iceberg tables function in Athena, see Using Iceberg tables in the Athena User Guide.
HealthLake supports READ operations of your HealthLake data stores data stores in Athena. To learn more about Create, Read, Update, and Delete (CRUD) operations using the FHIR REST API operations, see Using FHIR REST API operations with an AWS HealthLake data store to learn more about how CRUD operations affect your data in Athena.
The topics in this chapter describe how to connect your HealthLake data store to Athena, how to query it using SQL, and how to connect results with other AWS services for further analysis.
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