When Should I Use GaussDB(DWS) and MRS?
MRS works better with big data processing frameworks such as Apache Spark, Hadoop, and HBase, to process and analyze ultra-large datasets using custom code. MRS enables you to control cluster configurations and the software installed in the cluster.
GaussDB(DWS) works better with complex queries of large amounts of structured data. GaussDB(DWS) aggregates data from multiple sources, such as inventory, finance, and retail sales systems. To ensure data consistency and accuracy, GaussDB(DWS) stores data in a highly structured manner. This structure builds data consistency rules directly into database tables. Additionally, GaussDB(DWS) is highly compatible with standard SQL statements and syntax used in traditional databases.
GaussDB(DWS) is an ideal choice for performing complex queries on massive collections of structured data, with superb performance.
General Problems FAQs
- Why Do I Need to Use a Data Warehouse?
- Why Should I Use Public Cloud GaussDB(DWS)?
- Should I Choose Public Cloud GaussDB(DWS) or RDS?
- What Are the Differences Between Users and Roles?
- When Should I Use GaussDB(DWS) and MRS?
- How Do I Check the Creation Time of a Database User?
- Regions and AZs
- Is My Data Secure in GaussDB(DWS)?
- How Is GaussDB(DWS) Secured?
- Can I Modify the Security Group of a GaussDB(DWS) Cluster?
- How Are LibrA, GaussDB A, and GaussDB(DWS) Related?
- What Is a Database/Data Warehouse/Data Lake/Lakehouse?
- How Are Dirty Pages Generated in GaussDB(DWS)?
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