Updated on 2024-04-03 GMT+08:00

Versions

Select a DataArts Studio version with caution based on the functions and specifications you need.
  • After you buy an instance of a specified version, you cannot directly downgrade the version. For example, if you have bought an instance of the enterprise version, you cannot directly downgrade the instance to the starter version. Instead, you will need to back up data of the instance, unsubscribe from it, buy a new instance, and migrate the backup data to the new instance.
  • If your business volume keeps increasing and the instance version you have bought cannot meet your requirements, you can upgrade the instance version. To upgrade the instance version, log in to the DataArts Studio console, locate the target DataArts Studio instance, click Upgrade, and buy a package with higher specifications.

Application Scenarios of DataArts Studio Versions

Table 1 Recommended application scenarios for each DataArts Studio version

Version

Application Scenario

Starter

A primary data lake project with no full-time data development engineers and no data governance needs

Basic

One or two full-time data development engineers, and up to 1,000 data tables

Advanced

Five to ten full-time data development engineers, clear data standards and efficient data quality management, and up to 2,000 data tables

Professional

Large or medium enterprises with a team of 10 to 30 full-time data development engineers and well-designed systems

Enterprise

Large enterprises and enterprises with multiple branches

Specifications of DataArts Studio Versions

Table 2 Components supported by DataArts Studio

DataArts Studio Component

Starter

Basic

Advanced

Professional

Enterprise

DataArts Migration

Management Center

DataArts Architecture

x

DataArts Factory

DataArts Quality

x

DataArts Catalog

x

DataArts DataService

x

DataArts Security

x

Table 3 DataArts Studio version specifications (a single instance)

Specification

Starter

Basic

Advanced

Professional

Enterprise

DataArts Studio CDM cluster[1]

Number of clusters: 1

Name: cdm.medium

vCPUs | memory: 4 vCPUs | 8 GB

Number of clusters: 1

Name: cdm.medium

vCPUs | memory: 4 vCPUs | 8 GB

Number of clusters: 1

Name: cdm.large

vCPUs | memory: 8 vCPUs | 16 GB

Number of clusters: 1

Name: cdm.xlarge

vCPUs | memory: 16 vCPUs | 32 GB

Number of clusters: 1

Name: cdm.xlarge

vCPUs | memory: 16 vCPUs | 32 GB

Job node scheduling times/day[2]

5,000/day

20,000/day

40,000/day

80,000/day

200,000/day

Number of technical assets[3]

Not supported

1,000

2,000

4,000

10,000

Number of data models[4]

Not supported

1,000

2,000

4,000

10,000

Notes:

[1] DataArts Studio CDM cluster: This is a free cluster provided together with the DataArts Studio instance. It can be used as an agent for the data connections in Management Center. However, you are not advised to use the node in a data migration job when the node is used as an agent. To buy a CDM cluster used to run CDM jobs, buy a CDM incremental package. For details, see Buying a DataArts Studio Incremental Package.

[2] Job node scheduling times/day: It refers to the total number of scheduling times of the data development jobs, quality jobs, comparison jobs, scenarios, and metadata collection jobs per day. The number of scheduling times of data development job per day is measured by node (including the Dummy node), covering PatchData tasks but not test or retry upon failures. For example, if a job contains two DWS SQL nodes and one Dummy node, starts to be executed at 00:00 every day, is scheduled every 10 hours, and a PatchData task is performed on the current day to patch data of the last 10 days, then the number of scheduling times of the job is 66 (2 x 3 + 2 x 3 x 10) for the current day and 6 (2 x 3) for every following day.

In addition, if the number of used scheduling times, scheduling times in use, and scheduling times to be used for job nodes on the current day exceeds the specifications of this version, a message is displayed, indicating that the number of job node scheduling times/day exceeds the quota.

[3] Number of technical assets: number of tables and OBS files in DataArts Catalog

[4] Number of data models: number of logical models, physical models, dimension tables, fact tables, and summary tables in DataArts Architecture.