An e-commerce company needs to store the complete clickstream generated by its website. Each event arrives as a semi-structured JSON document whose set of fields can change often as new marketing experiments roll out. The data layer must automatically distribute writes across many inexpensive servers to absorb sudden traffic spikes, yet the analysts do not require complex joins or multi-row ACID transactions. Given these requirements, which database type is the most appropriate choice?
A non-relational (NoSQL) document database is designed to ingest and query JSON-like documents that may differ in structure, so it handles the rapidly evolving clickstream schema without costly ALTER TABLE operations. Document stores also include built-in sharding and replication, letting the system scale horizontally across commodity nodes to keep pace with unpredictable surges in event volume. Relational databases impose a fixed schema and usually scale vertically, making them harder to adapt and distribute for this workload. In-memory OLAP cubes are optimized for aggregated analytical queries on pre-processed data, not for high-velocity operational writes. Spreadsheets (even when saved as CSV files) lack transactional guarantees, concurrency controls and distributed scalability, so they cannot serve as a reliable clickstream data store.
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CompTIA Data+ DA0-002 (V2)
Data Concepts and Environments
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