Companies using large SAP HANA instances in the cloud face significant challenges due to the continuous growth of their databases.
Unlike other cloud services that allow horizontal scaling, SAP HANA operates primarily with vertical scaling, presenting unique challenges. This ZTalent blog will explore these challenges and propose effective strategies to address them.
Scalability and Cloud Challenges
Cloud scalability allows for capacity adjustment according to demand. However, SAP HANA requires larger instances, presenting challenges. Although instances up to 24 TB are available, larger companies need even more capacity, increasing availability risks and costs.
Data Management Strategies
To tackle these challenges, companies can implement a clearly defined data management strategy from the outset. These strategies include data organization and archiving, using SAP NSE, partitioning, and employing SAP DLM.
Data Organization and Archiving
Data archiving involves moving historical or less frequently accessed data to secondary storage systems. This process frees up space in SAP HANA and keeps data available for ad hoc queries. The main advantages of data archiving include:
- Storage Cost Reduction: Moving inactive data to separate storage reduces cloud storage costs.
- Performance Improvement: Freeing up space in the HANA database enhances overall performance.
- Compliance and Retention: Proper archiving ensures data is retained according to compliance requirements and retention policies.
- Efficient Archiving Strategy: Planning and implementing an effective archiving strategy ensures the process is systematic and beneficial.
Using SAP NSE (Native Storage Extension)
SAP HANA NSE allows organizations to manage less frequently accessed data without fully loading it into memory. It combines disk-based database technology with HANA’s in-memory capability. The benefits of SAP NSE include:
- Memory Footprint Reduction: Storing less data in memory helps manage data growth without increasing costs.
- Simple Implementation: Activating NSE on selected tables requires less effort than other strategies and does not affect data visibility.
- Memory Optimization: NSE marks infrequently accessed data as “page-loadable,” loading them only when needed for queries.
Partitioning
Data partitioning in SAP HANA is an effective strategy that allows for faster and parallel operations. The benefits of partitioning include:
- Improved Scalability and Efficiency: Enhances the scalability and efficiency of HANA systems.
- Performance Enhancement: Results in lower response times and more efficient processing.
- Manageable Systems: Helps create smaller, more cost-effective HANA systems.
SAP DLM (Data Lifecycle Management)
SAP DLM manages data temperature by classifying data as “cold” or “hot” based on usage, allowing companies to reduce growth costs by directly connecting to a Spark Cluster.
Companies using SAP HANA in the cloud face the challenge of continuous database growth. To manage this effectively, it is crucial to implement a well-defined data management strategy that ensures SAP HANA remains a viable and scalable solution for the future, optimizing performance and reducing costs in the cloud.
