How does column-based storage allow SAP HANA to read data faster? Note: There are 2 correct answers to this question

Question

Options

• AA column can be processed at the same time by different CPU cores.
• BA column is managed in a compressed way
• CA column is read-optimized by reading from the delta store only
• DA column contains all of the information for one record.

• A
  95% (58)
• C
  3% (2)
• D
  2% (1)

Explanation

Column-based storage enables faster reads in SAP HANA because each column holds values of the same data type, which compresses extremely well (B) - reducing I/O and fitting more data in memory. Additionally, since a column's values are stored contiguously, multiple CPU cores can process different chunks of the same column simultaneously via parallel execution (A), dramatically speeding up analytical queries like SUM or AVG.

Why the distractors are wrong:

• C is backwards - the delta store is a write-optimized row store for recent changes; reads are merged from both the main column store and the delta store, not the delta store alone.
• D describes row-based storage, where a single record's fields are stored together. Column stores do the opposite - one column holds one field across all records.

Memory tip: Think "column = one attribute for everyone" (vertical slice). This lets HANA compress similar values together (B) and parallelize scanning across cores (A) - both are wins for analytical read performance.

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