SAP SAP HANA Syllabus

SAP HANA syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for SAP HANA in SAP, not a summary of it.

1. 1

   Introduction to SAP HANA

   2 topics

   • Overview
     • What is SAP HANA?
     • History and Evolution
     • Key Features
   • Architecture
     • In-Memory Computing
     • Columnar Storage
     • Database Design
2. 2

   SAP HANA Installation and Configuration

   3 topics

   • System Requirements
     • Hardware Requirements
     • Operating System Compatibility
   • Installation Steps
     • Pre-Installation Checklist
     • Installation Procedure
     • Post-Installation Configuration
   • System Configuration
     • Initial Setup
     • User Management
     • Backup and Recovery
3. 3

   Data Modeling in SAP HANA

   3 topics

   • Core Concepts
     • Attribute Views
     • Analytic Views
     • Calculation Views
   • Advanced Data Modeling
     • SQLScript
     • Procedures and Functions
     • Table Functions
   • Optimization Techniques
     • Performance Tuning
     • Best Practices
     • Debugging and Troubleshooting
4. 4

   SAP HANA Administration

   3 topics

   • System Monitoring
     • HANA Studio
     • HANA Cockpit
     • SAP Solution Manager
   • Security Management
     • User Authentication
     • Authorization
     • Encryption
   • Database Management
     • Backup and Recovery
     • High Availability
     • Disaster Recovery
5. 5

   SAP HANA Development

   3 topics

   • Development Tools
     • SAP Web IDE
     • Eclipse
     • HANA Studio
   • Application Development
     • XS Engine
     • OData Services
     • SAPUI5
   • Integration
     • SAP BW
     • SAP ERP
     • Third-Party Tools
6. 6

   Advanced Topics in SAP HANA

   3 topics

   • Predictive Analytics
     • PAL (Predictive Analysis Library)
     • R Integration
     • Machine Learning
   • Big Data Integration
     • Hadoop Integration
     • Spark Integration
     • Data Lake
   • Internet of Things (IoT)
     • IoT Services
     • Real-Time Data Processing
     • Edge Computing

SAP HANA flashcards for SAP

18 of 86 cards from the SAP HANA deck — real questions with worked answers.

1. What is SAP HANA?

   SAP HANA (High-performance ANalytic Appliance) is an in-memory, column-oriented relational database management system that combines OLTP and OLAP processing in a single platform, storing data primarily in RAM for real-time analytics and transactions.

2. What does the acronym HANA stand for?

   High-performance ANalytic Appliance.

3. What are the two main advantages of an in-memory database like SAP HANA over a traditional disk-based database?

   (1) Data resides in RAM, eliminating slow disk I/O for read/write, giving orders-of-magnitude faster access; (2) it enables real-time analytics on live transactional data (HTAP) without a separate data warehouse.

4. In SAP HANA, what is the difference between row store and column store?

   Row store keeps all values of a record together (good for frequent single-record OLTP writes); column store keeps all values of a column together (good for analytical reads, aggregation, and high compression). HANA defaults to column store.

5. Why does column-store organization enable better compression in SAP HANA?

   Because values within a single column are of the same data type and often repetitive, allowing efficient techniques like dictionary encoding and run-length encoding, achieving high compression ratios.

6. What is dictionary encoding in SAP HANA?

   A compression technique where distinct column values are stored once in a sorted dictionary and each row stores a compact integer value-ID (position) referencing that dictionary, reducing storage and speeding up scans.

7. What are the two storage areas of a SAP HANA column table, and their purpose?

   The main store (read-optimized, compressed, sorted dictionary) and the delta store (write-optimized for fast inserts/updates). The delta merge process periodically merges delta into main.

8. What is the delta merge operation in SAP HANA?

   The process that moves new/changed data from the write-optimized delta store into the read-optimized, compressed main store, rebuilding the sorted dictionary to keep queries fast.

9. Which processing engine executes SQL and calculation logic in SAP HANA?

   The Index Server, which contains the main data engines (Join Engine, OLAP Engine, Calculation Engine) plus the SQL processor, transaction manager, and persistence layer.

10. Name the three main data-processing engines inside the SAP HANA Index Server.

    The Join Engine (SQL/joins on column tables), the OLAP Engine (aggregation on analytic/star-schema data), and the Calculation Engine (complex calculation views and stored logic).

11. What is the role of the Name Server in SAP HANA architecture?

    It knows the system topology (which data resides on which node) and manages landscape information in a distributed/scale-out HANA system.

12. What is the persistence layer in SAP HANA and why is it needed for an in-memory database?

    It writes data and log to disk via data volumes (savepoints) and log volumes so data survives power loss or restart; in-memory data is periodically persisted and can be recovered.

13. What are savepoints in SAP HANA persistence?

    Periodic operations (default every ~5 minutes) that flush changed in-memory data pages to the data volume on disk, providing a consistent recovery point together with the redo log.

14. What is the SAP HANA XS (Extended Application Services) component?

    An application server embedded in HANA. XS Classic (older, embedded in index server) and XS Advanced (XSA, based on Cloud Foundry) let developers build and run web applications directly on the HANA platform.

15. What is the primary CPU architecture requirement for an on-premise SAP HANA server?

    Intel x86-64 processors (certified Intel Xeon families) or IBM Power (POWER8/9/10) for certain deployments; the platform requires 64-bit certified hardware.

16. What is the general recommended ratio of RAM sizing relative to data in SAP HANA?

    Roughly, main memory should be about twice the size of the compressed column-store data ($RAM \approx 2 \times \text{data size}$) to accommodate the data plus workspace for queries, temporary results, and delta.

17. For SAP HANA persistence, how are the data volume and log volume typically sized relative to RAM?

    Data volume $\approx 1.2 \times$ RAM (net data area) and log volume sized to at least $\approx 0.5 \times$ RAM (min 512 GB for larger systems), ensuring durability and recovery.

18. Which operating systems are supported for on-premise SAP HANA?

    SUSE Linux Enterprise Server (SLES for SAP Applications) and Red Hat Enterprise Linux (RHEL for SAP), both 64-bit Linux distributions.

See more SAP HANA flashcards →

Planning SAP HANA for SAP

SAP HANA (SAP) FAQ