What characterizes a Row Table in SAP HANA?

What characterizes a Row Table in SAP HANA?

• A. A table that stores data in rows, suitable for read-heavy operations
• B. A table that stores data in columns optimized for analytics
• C. A table that stores data in rows, suitable for write-heavy workloads
• D. A special temporary table for intermediate calculations

Answer: (C)

A Row Table in SAP HANA is characterized by its storage of data in a row-based format, making it particularly efficient for certain types of workloads. This structure is optimal for write-heavy operations, such as transaction processing or environments where frequent updates and inserts are needed. In row-oriented tables, data is stored such that all the information for a single record is contained within one row, allowing for quick access and modifications to that specific record. This format is beneficial when queries are expected to retrieve or manipulate complete records, which is common in operational systems. While other types of tables, such as column tables, are designed for analytics and read-heavy operations, row tables excel in scenarios requiring efficient transaction processing and immediate data changes. Additionally, the creation of temporary tables serves a different purpose and is not the primary focus of typical row table usage in relation to data processing workflows.

A Row Table in SAP HANA is characterized by its storage of data in a row-based format, making it particularly efficient for certain types of workloads. This structure is optimal for write-heavy operations, such as transaction processing or environments where frequent updates and inserts are needed.

In row-oriented tables, data is stored such that all the information for a single record is contained within one row, allowing for quick access and modifications to that specific record. This format is beneficial when queries are expected to retrieve or manipulate complete records, which is common in operational systems.

While other types of tables, such as column tables, are designed for analytics and read-heavy operations, row tables excel in scenarios requiring efficient transaction processing and immediate data changes. Additionally, the creation of temporary tables serves a different purpose and is not the primary focus of typical row table usage in relation to data processing workflows.