DP-900 Describe core data concepts Practice Question
You are designing a data solution for a retail company that needs to store transactional data (orders, payments) with strong consistency and support for complex joins. The data volume is moderate but expected to grow. Which Azure service should you choose?
⚠ Common exam trap
A common mix-up: candidates confuse 'scalability' with 'suitability for transactional workloads' and choose Cosmos DB for its global distribution, overlooking that strong consistency and complex joins are not its core strengths.
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 SQL Database
Azure SQL Database is a fully managed relational database that provides ACID transactions with strong consistency and supports complex joins via T-SQL. It is ideal for transactional workloads like orders and payments where data integrity and relational queries are critical, and it scales elastically to accommodate growing data volumes.
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 Cosmos DB
Why it's wrong here
Azure Cosmos DB is a globally distributed, multi-model NoSQL database that offers multiple consistency models and a SQL-like query API. However, it does not enforce schema, referential integrity, or foreign keys, and its query engine's support for multi-table joins is extremely limited (typically only within a logical partition). This makes it a poor fit for transactional retail workloads that require complex relational queries and strict ACID guarantees, unlike a fully relational database management system.
- ✗
Azure Table Storage
Why it's wrong here
Azure Table Storage is a massively scalable NoSQL key-value store where each entity is accessed via a partition key and row key. It provides essentially no relational capabilities—no joins, no foreign keys, no transactions spanning multiple entities, and no complex query optimizer. Because a retail transactional solution typically needs linked data (customers, orders, products) with atomic consistency, Azure Table Storage is unsuitable for this scenario and is better reserved for simple, high-volume telemetry or lookup data.
- ✓
Azure SQL Database
Why this is correct
Azure SQL Database is a fully managed PaaS relational database built on the SQL Server engine, offering the full T-SQL language, complex joins, stored procedures, and ACID-compliant transactions. It delivers strong consistency by default, guaranteeing that every query sees the latest committed data, which is essential for retail operations like order management and inventory control. Its relational and transactional capabilities make it the natural choice for a transactional data solution that does not require the massive scale-out of analytics engines.
- ✗
Azure Synapse Analytics
Why it's wrong here
Azure Synapse Analytics is a unified analytics platform that combines data warehousing, big data, and data integration, relying on a massively parallel processing (MPP) architecture. While its SQL pool supports T-SQL, it is optimized for columnar scans and large aggregations, not for the row-level, high-concurrency, low-latency updates characteristic of transactional OLTP workloads. Using Synapse for a retail transactional database would result in poor performance for point queries and limited transactional integrity, so it is not the correct answer.
Go deeper
Related to this question
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Data Roles and Core Concepts
Key term
Azure SQL Database
Azure SQL Database is a fully managed relational database-as-a-service (DBaaS) in Microsoft Azure, based on the SQL Server engine, that handles scaling, backups, patching, and high availability automatically.
Key term
Transactional data
Transactional data is information that captures a specific event or exchange, such as a sale, a payment, or a system log entry, and is recorded in a database or log system.
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