AnalyticDB for MySQL provides extract, transform, and load (ETL) of data processing, real-time online analysis, core reports, dashboards, and monitoring capabilities for tens of thousands of enterprises. It provides stable offline and online data services for businesses and consumers. This topic describes five scenarios in which AnalyticDB for MySQL is used: real-time data warehouses, precision marketing, business intelligence (BI) reports, multi-source joint analysis, and interactive query.

Real-time data warehouses

This scenario requires a unified platform for online query and offline computing to simplify the data architecture and reduce development and O&M costs. This scenario supports a more reasonable resource ratio by using Auto Scaling to reduce the amount of retained resources during off-peak hours, optimize costs, and improve cost-effectiveness.

The following benefits are provided for this scenario:

Task integration for online and offline data processing
Data can be added, deleted, and modified in real time. Online analysis is integrated with ETL computing to integrate big data services with database services. Online and offline tasks are isolated by resource groups to ensure business stability.
Elastic computing and storage resources
The compute-storage separation architecture allows on-demand scaling of computing and storage resources. This utilizes resources in a more fine-grained manner and reduces costs.

Precision marketing

In this scenario, the growth, activity, and retention of users in different channels are monitored by using real-time statistics. This allows enterprises to analyze the return on investment (ROI) in a quick manner, improves the data timeliness of marketing effects, improves product experience, optimizes marketing plans, and increases the overall revenue.

The following benefits are provided for this scenario:

Real-time synchronization of data from a variety of sources
Structured and unstructured data from data sources of multiple businesses can be synchronized in real time.
Real-time feedback of marketing effects
Real-time complex contextual computing is supported for large amounts of log and business data, which improves the feedback timeliness of marketing effects.

BI reports

This scenario requires support for real-time warehousing and computing of large amounts of data, return of results within milliseconds or seconds, and convenient and flexible creation of reports. A wide range of visual BI tools can be used to help developers use BI reports to lower the threshold for digital construction of enterprises.

The following benefits are provided for this scenario:

Access to Realtime Compute in real time
Up to millions of records can be written per second and updates are visible in real time. Report queries can respond within milliseconds or seconds.
High compatibility with the BI ecosystem
AnalyticDB for MySQL is highly compatible with MySQL protocols and the SQL:2003 standard and supports dozens of mainstream BI tools such as Tableau, FineReport, and Quick BI.

Multi-source joint analysis

In this scenario, data synchronization links must be configured for enterprises to build data warehouses on the cloud and complex data analysis that arises from sharding must be solved so that you can focus more on the business logic.

The following benefits are provided for this scenario:

Access of multiple data sources
Data can be imported from database services such as ApsaraDB RDS, PolarDB-X, PolarDB, Oracle, and SQL Server, big data platforms or services such as Flink, Hadoop, E-MapReduce (EMR), and MaxCompute, Object Storage Service (OSS), log platforms or services such as Kafka and Log Service, and on-premises sources.
Quick creation of warehouses
Data from ApsaraDB RDS, PolarDB for MySQL, or a Logstore in Log Service can be synchronized to an AnalyticDB for MySQL cluster with simple configurations. Data from databases and tables can be aggregated to the same table for global analysis.

Interactive query

This scenario requires support for real-time BI reports and custom multi-dimensional queries with smooth responses and optimal interactive experience. Analysis dimensions can be chosen without the need of modeling and computing in advance, which facilitates exploratory analysis.

The following benefits are provided for this scenario:

Fast query
Join query results can be returned within milliseconds or seconds and applications run smoothly without being stuck, which ensures satisfactory user experience.
Support for complex SQL statements
Complex join queries can be performed on data in dozens of tables or thousands of rows.