DP-203 Design and implement data storage Practice Question
A healthcare organization needs to store electronic health records (EHR) in a format that supports schema flexibility and complex nested data. The solution must allow fast queries by patient ID and enable analytics with Azure Synapse. Which data store should you choose?
⚠ Common exam trap
Watch out — candidates often choose Azure SQL Database with JSON columns (Option D) because they assume relational databases can handle JSON, but they overlook the requirement for schema flexibility and native analytical store integration, which Cosmos DB with analytical store uniquely provides for hybrid transactional/analytical processing (HTAP) workloads.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Cosmos DB with analytical store enabled
Azure Cosmos DB with analytical store enabled is the correct choice because it provides schema flexibility for complex nested EHR data, supports fast point reads by patient ID via its indexed partition key, and the analytical store enables efficient analytics with Azure Synapse through the Synapse Link feature, which automatically synchronizes operational data into a columnar format optimized for large-scale queries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Table Storage
Why it's wrong here
Table Storage stores flat entities keyed by partition and row, so nested EHR structures must be flattened or serialised, and Synapse cannot query it natively without copying data out. It fits cheap key-value lookups at scale, not complex nested analytics.
- ✗
Azure Data Lake Storage Gen2 with files in JSON format
Why it's wrong here
JSON files in Data Lake Storage hold nested, schema-flexible records, yet queries filtering by patient ID scan files rather than seeking an index, so fast point lookups fail. It suits landing raw semi-structured data for later Synapse transformation, not indexed record retrieval.
- ✓
Azure Cosmos DB with analytical store enabled
Why this is correct
Azure Cosmos DB with analytical store enabled satisfies the schema-flexibility and nested-data requirements through its schema-agnostic JSON document model, while partitioning on patient ID delivers fast point reads. The analytical store provides columnar, Synapse-linked querying without impacting transactional throughput, meeting the analytics constraint.
- ✗
Azure SQL Database with JSON columns
Why it's wrong here
JSON columns give schema flexibility, but Azure SQL Database enforces a relational schema and its JSON support lacks the distributed columnar engine Synapse uses for large analytical scans. It is the right choice for transactional EHR records needing ACID guarantees, not petabyte-scale analytics.
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