SAP HANA Persistence Layer

SAP HANA Persistence Layer

SAP HANA persistence layer manages logging of all the transactions in order to provide standard backup and restore functions. Both the row stores and column stores tables interact with the persistence layer.

The persistence layer manages both data and log volumes on the physical drive.
It offers regular savepoints, By default save point value is 300 seconds. So, for every 300 seconds the changes made in the memory will be updated in physical drive. You can also customized savepoint value.
The savepoints are also triggered by several other operations such as data backups, a database shutdown or after a restart is completed.

Disk storage is still required to allow restarts in case of power failure and for permanent persistence. The SAP HANA persistence layer stores data in persistent disk volumes that are organized in pages. It is divided in both the log and data area.

Data changes are saved on disk immediately in the logs (synchronously). This is required to make a transaction durable. It is not necessary to keep the entire data, but the transaction log can be used to replay changes after a crash or database restart.

At regular intervals (standard: every five minutes), a new savepoint is created. That is, all of the pages that were changed are refreshed in the data area of the persistence layer.

Changes are written to the Data Volumes asynchronously, the user or application does not need to wait for this.

To optimize the performance, fast storage is used for the log area. For example, it uses solidstate drives (SSDs) or Fusion-io drives.

Data volume contains file in which data is organized into pages ranging in size from page size 4KB to 16MB. Data is written to and loaded from the data volume by page. Over time, pages are created, changed, and deleted. The size of the data file is increased automatically as more space is required.

However, it is not decreased automatically when less space is required. This means that, at any given time, the actual payload of a data volume may be less than its total size.