Question: What is SAP HANA Data Tiering?

Answer

SAP HANA data tiering is a strategy for managing and optimizing the storage of data within the SAP HANA in-memory database. This approach categorizes data into different tiers based on its frequency of access, business criticality, and performance requirements, thereby reducing costs and improving overall system efficiency.

Data Tier Classification

SAP HANA data tiering typically involves three main data tiers: hot, warm, and cold.

• Hot Data: This is the most frequently accessed data, critical for real-time processing and analytics. It is stored in-memory within SAP HANA to ensure high performance.

  • Characteristics: High frequency of access, high performance requirements, and high business criticality.
  • Storage: In-memory on SAP HANA.

• Warm Data: This data is less frequently accessed but still needs to be managed as part of the SAP HANA database. It is stored on disk, which is more cost-effective than in-memory storage.

  • Characteristics: Medium frequency of access, medium performance requirements, and medium business criticality.
  • Storage: On disk using solutions like SAP HANA Native Storage Extension (NSE) or SAP HANA extension nodes.

• Cold Data: This is the least frequently accessed data, often legacy or archival data. It is stored on low-cost storage solutions outside the SAP HANA system but remains accessible.

  • Characteristics: Low frequency of access, low performance requirements, and low business criticality.
  • Storage: On external storage solutions such as SAP IQ, Hadoop, Azure Data Lake, or SAP Big Data Services.

Implementation and Tools

Several tools and methodologies are available to implement data tiering in SAP HANA:

• SAP HANA Dynamic Tiering: An add-on to the SAP HANA database that allows moving data from in-memory to disk-based storage, creating extended tables and multistore tables.
• SAP HANA Native Storage Extension (NSE): Introduced with SAP HANA 2.0 SPS 04, NSE allows adding warm data storage on disk, increasing data capacity at a lower total cost of ownership (TCO).
• SAP Data Lifecycle Management (DLM): Provides tools to manage the lifecycle of data, relocating it from hot to warm or cold storage based on aging rules.
• SAP Data Intelligence: Enables the integration of SAP HANA with external storage systems like Azure Data Lake Storage, facilitating the movement of cold data.

Benefits and Use Cases

Data tiering in SAP HANA offers several benefits:

• Cost Reduction: By moving less frequently accessed data to lower-cost storage tiers, organizations can reduce their TCO and SAP HANA licensing costs.
• Performance Optimization: Ensures that high-value, frequently accessed data remains in-memory for optimal performance, while less critical data is stored on more cost-effective storage.
• Scalability: Allows for the efficient management of growing data volumes by leveraging different storage tiers.

Example Scenarios

1. SAP HANA Cloud:

   • In SAP HANA Cloud, data can be split between hot, warm, and cold tiers. Hot data is stored in-memory, warm data on disk using Native Storage Extension (NSE), and cold data in an integrated data lake.
   • The data lake in SAP HANA Cloud can store structured and unstructured data, providing excellent performance for analytics across large volumes of data.

2. SAP BW/4HANA:

   • SAP Data Tiering Optimization in SAP BW/4HANA allows classifying data as hot, warm, or cold based on cost and performance requirements. Data is stored in different storage areas accordingly.
   • External Tier (cold) data can be stored in SAP IQ, Hadoop, or SAP Vora, while warm data is stored in SAP HANA extension nodes.

By implementing a data tiering strategy, organizations can optimize their SAP HANA environment, ensuring high performance for critical data while managing costs effectively.