A company stores customer names, addresses, and order history. They need to perform complex queries that join customer and order data. Which type of data store is most appropriate for this scenario?
Trap 1: Key-value store
Key-value stores are designed for simple lookups by key and do not support complex join queries across multiple datasets.
Trap 2: Document database
Document databases store semi-structured data (e.g., JSON) and although they can embed related data, they are not optimized for join-heavy queries across collections.
Trap 3: Graph database
Graph databases are built for highly interconnected data and relationship traversal, but they are not the standard choice for tabular join operations typical of relational workloads.
- A
Key-value store
Why wrong: Key-value stores are designed for simple lookups by key and do not support complex join queries across multiple datasets.
- B
Relational database
Relational databases organize data into tables with defined schemas and support SQL queries including joins, making them ideal for this requirement.
- C
Document database
Why wrong: Document databases store semi-structured data (e.g., JSON) and although they can embed related data, they are not optimized for join-heavy queries across collections.
- D
Graph database
Why wrong: Graph databases are built for highly interconnected data and relationship traversal, but they are not the standard choice for tabular join operations typical of relational workloads.