Challenges

  • Unsatisfying timeliness

    Volkswagen 4S stores need their data reports to be automatically compared every night. The timeliness and data governance do not meet the requirements of MEP service reports.

    Volkswagen 4S stores need their data reports to be automatically compared every night. The timeliness and data governance do not meet the requirements of MEP service reports.

  • High maintenance costs

    In the original solution, a synchronization link was created for each source table. Each schema had many tables to be synchronized, leading to high cost of data synchronization links.

    In the original solution, a synchronization link was created for each source table. Each schema had many tables to be synchronized, leading to high cost of data synchronization links.

  • Storage bottleneck

    As the company business grew, the MEP report system required more than 10 TB of storage, but the original database does not meet the requirement.

    As the company business grew, the MEP report system required more than 10 TB of storage, but the original database does not meet the requirement.

Solutions

  • Data synchronization

    A database synchronization tool has been used to aggregate different data sources to the same database and synchronize data from the cloud database to the on-premises big data platform CDH.

    A database synchronization tool has been used to aggregate different data sources to the same database and synchronize data from the cloud database to the on-premises big data platform CDH.

  • Performance and scalability

    GaussDB(for MySQL) provides up to 128 TB of storage and millions of QPS. It can rapidly process large volumes of concurrent data.

    GaussDB(for MySQL) provides up to 128 TB of storage and millions of QPS. It can rapidly process large volumes of concurrent data.

  • Reliability and availability

    GaussDB(for MySQL) decouples storage from compute and supports three-copy data storage for strong consistency. In the event of instance faults, the failover can be completed within seconds, with an RPO of zero and an RTO of less than 10s.


    GaussDB(for MySQL) decouples storage from compute and supports three-copy data storage for strong consistency. In the event of instance faults, the failover can be completed within seconds, with an RPO of zero and an RTO of less than 10s.

Benefits

  • Real-time reports

    The availability time of sales report data is reduced from 1 day to 1 minute.

    The availability time of sales report data is reduced from 1 day to 1 minute.

  • Reduced O&M costs

    DRS synchronizes data by instance.

    DRS synchronizes data by instance.

  • Data security and reliability

    The data synchronization delay is short. DRS eliminates the data inconsistency that may occur during data synchronization.

    The data synchronization delay is short. DRS eliminates the data inconsistency that may occur during data synchronization.

  • Large capacity, high performance, and scale-out in seconds

    DRS can quickly handle large amounts of concurrent data and scale out in seconds to easily cope with traffic spikes.

    DRS can quickly handle large amounts of concurrent data and scale out in seconds to easily cope with traffic spikes.