SAP HANA

DataArts Migration supports cloud-based RDS SAP HANA and on-premises SAP HANA data sources. It supports the 2.00.050.00.1592305219 version and meets the data synchronization requirements in different deployment environments.

Preparation and Constraints

Network requirements
The SAP HANA data source can communicate with CDM. This ensures smooth data transmission. For details, see Enabling Network Connectivity.
Required permissions
Connection user permissions: The connection user must have the required permissions to read and write data. The permission requirements are as follows:
- Read permission: The account must have the read-only permission (SELECT) on the table to be synchronized so that data can be read securely and accurately.
- Write permission: The account must have the write permission (INSERT, DELETE, and UPDATE) on the table to be synchronized so that data can be correctly written to the destination table.
- Table creation and deletion permissions: If a data integration task involves creating or deleting tables, the account must have the CREATE TABLE or DROP TABLE permission. For example, the account must be assigned the DBA role.
- Role permissions: The connection user should have the CONNECT and RESOURCE role permissions to connect to the database and perform data operations.
- Note: By default, the SELECT permission on system metadata tables is granted to PUBLIC. If you revoke this permission, you must grant it to each group or user.

Supported Data Types

DataArts Migration supports the following field types and their common variants in SAP HANA 2.00.050.00.1592305219. This ensures that DataArts Migration can correctly read and write data.

Category	Field Type	SAP HANA Read	SAP HANA Write
Character	VARCHAR	√	√
	NVARCHAR	√	√
	TEXT	√	√
Integer	BIGINT	√	√
	TINYINT	√	√
	SMALLINT	√	√
Floating number	REAL	√	√
	DECIMAL	√	√
	FLOAT	√	√
	DOUBLE	√	√
Time	DATE	√	√
	TIME	√	√
	TIMESTAMP	√	√
	DATETIME	√	√
Large object	CLOB	√	√
Large object	NCLOB	√	√
Boolean	BOOLEAN	√	√
Binary	BLOB	√	√
Binary	VARBINARY	√	√

Supported Migration Scenarios

DataArts Migration supports the following offline synchronization modes:

Single table synchronization
DataArts Migration supports table/file synchronization in data ingestion into a data lake or data migration to the cloud.
Database and table shard synchronization
DataArts Migration supports synchronization of data from multiple databases and tables in data ingestion into a data lake or data migration to the cloud.
Entire DB migration
DataArts Migrations supports synchronization of data from an on-premises database in data ingestion into a data lake or data migration to the cloud.

Database and table shard synchronization and entire DB migration are not supported in all regions. The following table lists the supported SAP HANA migration scenarios.

Supported Migration Scenario	SAP HANA Single Table Read	SAP HANA Single Table Write	SAP HANA Database/Table Shard Read	SAP HANA Database/Table Shard Write	SAP HANA Entire DB Read	SAP HANA Entire DB Write
Supported	√	√	x	x	x	x

Core Capabilities

Connection configuration

Configuration Item	Supported	Description
User/AK	√	User authentication ensures connection security.
SSL encryption	x	SSL encryption ensures secure data transmission. Currently, this function is not supported.
SSL authentication	x	By default, certificate authentication is disabled.
Private certificate	x	Private certificates are not supported.
Connection configuration optimization	√	Connection configuration such as connectTimeout can be optimized to improve connection performance.
Custom driver	√	Custom drivers are supported and provide better flexibility.
Tenant database connection mode	x	Currently, the tenant database connection mode is not supported.

Read capabilities

Configuration Item	Supported	Description
Shard concurrency	√	Horizontal sharding based on primary keys or common fields and multi-thread concurrent extraction significantly improve the throughput and efficiency.
Dirty data processing	√	Abnormal data can be written to the dirty data bucket to prevent job failures caused by a small amount of abnormal data.
Custom fields	√	You can add computed columns, constant columns, or masking functions for tasks to meet personalized service requirements.
Incremental read	√	Where conditions and the SQL mode enable incremental data reading.
Stream and batch reading	Batch reading	Batch reading improves efficiency when there is a small or medium amount of data.
Optimization of the number of rows read	√	You can set Fetch Size in the connection to properly control the amount of data to be transmitted. This improves performance and prevents a transmission delay or the system from being overloaded when there is a large amount of data.
View reading	√	Data can be read from views. This enables flexible data integration and processing.

Write capabilities

Configuration Item	Supported	Description
Data source optimization parameters	√	Optimization parameters such as batchSize and socketTimeout are supported at the source. They improve write performance.
Dirty data processing	√	Abnormal data can be written to the dirty data bucket to prevent job failures caused by a small amount of abnormal data.
Conflict resolution	√	The Upsert primary key conflict resolution can be written.
Pre- and post-import processing	√	Operations such as preSql and delete can clean and process data before and after data import.
Concurrent write	√	Concurrent write improves efficiency.
Optimization of the number of written rows	√	You can set the number of rows written by each request in the connection to properly control the amount of data to be transmitted. This improves performance and prevents a transmission delay or the system from being overloaded when there is a large amount of data. This function is not supported for this data source.