Help Center> GaussDB(DWS)> Service Overview> Application Scenarios
Updated on 2024-04-25 GMT+08:00
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Application Scenarios

Data Warehouse Migration

The data warehouse is an important data analysis system for enterprises. As the service volume grows, performance of their own data warehouses cannot meet the actual service requirements due to scalability limitation and high costs. As an enterprise-class data warehouse on the cloud, GaussDB(DWS) features high performance, low cost, and easy scalability, satisfying requirements in the big data era.

Figure 1 Data warehouse migration

Advantages

  • Seamless migration

    GaussDB(DWS) provides various migration tools to ensure seamless migration of popular data analysis systems such as Teradata, Oracle, MySQL, SQL Server, PostgreSQL, Greenplum, and Impala.

  • Compatible with conventional data warehouses

    GaussDB(DWS) supports the SQL 2003 standard and stored procedures. It is compatible with some Oracle syntax and data structures, and can be seamlessly interconnected with common BI tools, saving service migration efforts.

  • Secure and reliable

    GaussDB(DWS) supports data encryption and connects to DBSS to ensure data security on the cloud. In addition, GaussDB(DWS) supports automatic full and incremental backup of data, improving data reliability.

Converged Big Data Analysis

Data has become the most important asset. Enterprises must be able to integrate their data resources and build big data platforms to mine the full value of their data. In predictive analysis use cases, massive volumes of data must be processed. Huawei GaussDB(DWS) delivers the needed processing power to handle these intense compute scenarios.

Figure 2 Converged big data analysis

Advantages

  • Unified Analysis Entrance

    The GaussDB(DWS) SQL serves as the unified entry of upper-layer applications, so that application developers can access all data using the SQL.

  • Real-Time Interactive Analysis

    Analysis personnel can obtain immediately actionable information from the big data platform in real time.

  • Auto Scaling

    Adding nodes allows you to easily expand into PB-range capacity while enhancing query and analysis performance of the system.

Enhanced ETL + Real-Time BI Analysis

The data warehouse is the pillar of the BI system for collecting, storing, and analyzing massive volumes of data. It powers business decision analysis for the IoT, finance, education, mobile Internet, and Online to Offline (O2O) industries.

Advantages

  • Data Migration

    Ability to import data in batches in real time from multiple data sources.

  • High Performance

    Cost-effective PB-level data storage and response to correlation analysis of trillions of data records within seconds.

  • Real-Time

    Real-time consolidation of service data to produce actionable insights in operational decision-making.

Figure 3 Enhanced ETL + real-time BI analysis

Real-Time Data Analysis

In the mobile Internet and IoT domains, huge volumes of data must be processed and analyzed in real time to extract the full data from data. The quick data import and query capabilities of GaussDB(DWS) accelerate data analysis to enable real-time ingestion, processing, and value generation.

Figure 4 Real-time data analysis

Advantages

  • Real-Time Import of Streaming Data

    Data from IoT and Internet applications can be written into GaussDB(DWS) in real time after being processed by the stream computing and AI services.

  • Real-Time Monitoring and Prediction

    Device monitoring, control, optimization, supply, self-diagnosis, and self-healing based on data analysis and prediction.

  • Converged AI Analysis

    Correlation analysis can be conducted on results of image and text data analysis by AI services and other service data on GaussDB(DWS).

  • E-commerce

    Huawei Vmall leverages GaussDB(DWS) as its database engine for data analysis. Data of online retailers is mainly used for marketing recommendation, operating and customer analysis, and full text search.

    Advantages of GaussDB(DWS) are as follows:

    • Multi-dimensional analysis: analysis from products, users, operation, regions, and more
    • Scale-out as the business grows: on-demand cluster scale-out as the business grows
    • High reliability: long-term stable running of the e-commerce system
  • IoT

    GaussDB(DWS) helps you analyze massive amounts of data from Internet of Things (IoT) in real time and perform optimization based on the results. It is widely used in industrial IoT, O2O service system, and IoV solutions.

    Advantages of GaussDB(DWS) are as follows:

    • Device monitoring and prediction: control, optimization, self-diagnosis, and self-healing based on data analysis, device monitoring, and behavior prediction
    • Information recommendation: tailed recommendation based on data of users' connected devices