What Are the Advantages of CDM?

Ease of use

You need to prepare server resources, and install and configure software, which is time-consuming.

Because the data source types are different, the program uses different access interfaces, such as JDBC and native APIs, to read and write data. In this case, various libraries and SDKs are required when you write data migration scripts, resulting in high development and management costs.

CDM provides a web-based management console for enabling services on web pages in real time.

You can migrate data by configuring data sources and migration jobs on the GUI and CDM will manage and maintain the data sources and migration jobs for you. In other words, you only need to focus on the data migration logic without worrying about the environment, which greatly reduces development and maintenance costs.

CDM also provides RESTful APIs to support third-party system calling and integration.

Real-time monitoring

You need to select specific versions to develop as required.

You can use Cloud Eye to automatically monitor CDM clusters in real time and manage alarms and notifications, so that you can keep track of CDM cluster performance metrics.

O&M free

You need to develop and optimize O&M functions, especially alarm and notification functions, to ensure system availability. Otherwise, manual attendance is required.

With CDM, you do not need to maintain resources such as servers and VMs. CDM has the log, monitoring, and alarm functions, which send notifications to related personnel in a timely manner to avoid 24/7 hours of manual O&M.

High efficiency

During data migration, the read and write process is completed in one job. Limited by available resources, the performance is poor and cannot meet the requirements of scenarios where massive sets of data need to be migrated.

Based on the distributed computing framework, CDM jobs are split into independent sub-jobs and executed concurrently, which drastically improves data migration efficiency. In addition, efficient data import interfaces are provided to import data from Hive, HBase, MySQL databases, and Data Warehouse Service (DWS).

Various data sources

Different tasks must be developed for different data sources, generating a number of scripts.

Data sources such as databases, Hadoop services, NoSQL databases, data warehouses, and files are supported.

Different network environments

As the cloud computing technology develops, user data may be stored in different environments, such as public clouds, on-premises or hosted Internet data centers (IDCs), and hybrid scenarios. In heterogeneous environments, data migration is subject to various factors, for example, network connectivity, which causes inconvenience for development and maintenance.

CDM helps you easily cope with various data migration scenarios, including data migration to the cloud, data exchange on the cloud, and data migration to on-premises service systems, regardless of whether the data is stored on on-premises IDCs, cloud services, third-party clouds, or self-built databases or file systems on ECSs.