SAP / SAP Mid Level (3 to 8 yrs) Interview questions
How does in-memory processing improve performance compared to traditional disk-based databases?
Disk I/O, even on fast SSDs, is dramatically slower than RAM access — often by two to three orders of magnitude. A traditional disk-based database mitigates this with caching, indexes, and pre-aggregated summary tables to avoid hitting disk on every query, but those techniques add complexity and can still fall behind disk when data isn't already cached.
-- traditional approach: rely on a pre-built aggregate table SELECT * FROM sales_summary_by_month; -- fast, but requires overnight batch job to build -- HANA approach: aggregate on the fly, directly against live transactional data SELECT region, SUM(amount) FROM sales_transactions GROUP BY region; -- fast even without pre-aggregation
Because HANA's data already lives in memory, it can compute aggregations and complex joins directly against live, current data on every query, without needing pre-built summary tables refreshed on a schedule — collapsing the traditional separation between "fast reporting on stale, pre-aggregated data" and "slow reporting on live, current data" into one system that does both.
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