AnalyticDB for MySQL supports real-time write operations with highly concurrent transactions per second (TPS), and allows you to perform quick analytics of large amounts of data by executing SQL statements. As an enterprise customer, you only need to migrate your data to AnalyticDB for MySQL. Then you can analyze the data and explore data values by executing standard SQL statements or using visualization tools. The most significant advantage of AnalyticDB for MySQL is the fast response to queries.
Construct classic real-time data warehouses
You can use Data Transmission Service to mirror the business tables in a relational database to AnalyticDB for MySQL. Then, you can use Quick BI to generate reports through drag-and-drop operations, or use DataV to customize a real-time data dashboard for your business.
- High construction efficiency
You can build real-time data warehouses through only some configurations.
- Strong analytics timeliness
After data is written into a relational database, DTS synchronizes the data to AnalyticDB for MySQL in real time. The latency of the data link is within one second.
- Simple and stable link architecture
The data is directly synchronized from the relational database to AnalyticDB for MySQL without passing through other systems, and no data loading is required. The link is short and clear.
- Low costs
Compared with the traditional offline extract-transform-load (ETL) process, the real-time data warehouse based on AnalyticDB for MySQL involves fewer components. It does not require the process of obtaining the data analysis result from other systems. ETL is integrated with interactive analytics at low costs.
Store real-time data cleansing results
Customers often store data cleansing results of a stream processing system in a traditional relational database deployed on a single server, such as a MySQL database. Then, the database is used as a report database. If the data volume of the database or a single table is too large, report queries become slow. AnalyticDB for MySQL can effectively resolve this issue. It supports hundreds of billions of data records in a single table. It allows you to fast query and analyze real-time reports that contain petabytes of data without any database and table sharding.
Store ETL data cleansing results
After data is cleansed on offline big data computing platforms such as MaxCompute, Spark SQL, Hadoop, and E-MapReduce, the reports are still complex, and data drilling is required. A database deployed on a single server does not have the capability to support such operations. In this case, a powerful report query engine such as AnalyticDB for MySQL is required.