Which statement best describes OLTP vs OLAP workloads and their typical query patterns?

• A. OLTP is used for analytical processing across large datasets; OLAP handles small transactions.
• B. OLTP and OLAP have identical query patterns.
• C. OLTP is classic batch processing; OLAP is real-time transactional.
• D. OLTP: short, frequent transactions; OLAP: long, complex analytical queries on large datasets.

Answer: (D)

OLTP vs OLAP differ in how they are used and what they optimize for. OLTP systems handle day-to-day operations with many short, fast transactions that update or read a small amount of data, demanding low latency and high concurrency. OLAP systems support analysis across large, historical datasets, using long-running, complex queries with aggregations, scans, and multi-table joins to enable reporting and business intelligence. This makes the description—OLTP having short, frequent transactions and OLAP having long, complex analytical queries on large datasets—the best fit. The other statements misstate the roles (OLTP isn’t for broad analytical processing across large datasets, OLAP isn’t about small transactions) and mix up batch vs real-time characteristics.