HANA data aging is a feature in SAP HANA that helps organizations manage their data more efficiently. As the amount of data stored in SAP HANA grows, it can become difficult and expensive to store all of it in memory. Data aging provides a way to move less frequently accessed data to lower-cost storage tiers while retaining the ability to access it quickly when needed. In this post, we’ll explore the benefits of data aging, how it works, and how to configure it in SAP HANA.

Benefits of Data Aging

Data aging offers several benefits to organizations, including:

1. Reduced storage costs: By moving less frequently accessed data to lower-cost storage tiers, organizations can reduce the amount of expensive memory they need to store their data. This can lead to significant cost savings over time.
2. Improved performance: By reducing the amount of data stored in memory, organizations can improve the performance of their SAP HANA applications. This is because less data needs to be processed, resulting in faster query and reporting times.
3. Simplified data management: Data aging can help organizations manage their data more efficiently by allowing them to focus on the data that is most important to their business. This can simplify data management and reduce the amount of time and effort required to maintain and backup their data.

How Data Aging Works

Data aging works by moving less frequently accessed data from the main memory tier to a lower-cost storage tier. In SAP HANA, this lower-cost storage tier is typically a disk-based storage system or an object store, such as Amazon S3 or Microsoft Azure Blob Storage. When data is moved to the lower-cost storage tier, it is still available for access, but it may take longer to retrieve than data that is stored in memory.

Data aging is typically configured based on data retention policies, which determine how long data should be stored in memory before it is moved to the lower-cost storage tier. These policies are typically based on the frequency of data access, with less frequently accessed data being moved to the lower-cost storage tier sooner than more frequently accessed data.

Configuring Data Aging in SAP HANA

To configure data aging in SAP HANA, you’ll need to follow these steps:

1. Define aging objects: Aging objects are used to define the data that will be aged. You’ll need to define aging objects based on the tables or partitions that contain the data you want to age.
2. Define aging policies: Aging policies are used to define how long data should be stored in memory before it is aged. You’ll need to define aging policies based on the retention requirements for your data.
3. Activate data aging: Once you’ve defined aging objects and policies, you’ll need to activate data aging for your SAP HANA database. This will start the process of moving less frequently accessed data to the lower-cost storage tier.

Conclusion

HANA data aging is a powerful feature that can help organizations manage their data more efficiently and cost-effectively. By moving less frequently accessed data to lower-cost storage tiers, organizations can reduce their storage costs, improve performance, and simplify data management. If you’re considering implementing data aging in your SAP HANA database, be sure to follow the steps outlined above to ensure a successful implementation.