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.

Real-time data warehouses

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

The following benefits are provided in this scenario:

Integration of tasks for online and offline data processing
In this scenario, 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 the business stability.
Elastic computing and storage resources
The compute-storage separation architecture allows you to scale out computing and storage resources. This makes resource utilization more fine-grained and reduces costs.

Precision marketing

This scenario monitors the growth, activity, and retention of users in different channels by using real-time statistics. This allows enterprises to quickly analyze the return on investment (ROI). This scenario improves the data timeliness of marketing effects, which improves product experience and optimizes marketing plans, and increases the overall revenues.

The following benefits are provided in this scenario:

Real-time synchronization of data from a variety of sources
This scenario supports data sources of multiple businesses and real-time synchronization of structured and unstructured data.
Real-time feedback of marketing effects
This scenario supports real-time complex contextual computing for large amounts of log data and businesses. This improves the feedback timeliness of marketing effects.

Business intelligence report

This scenario requires real-time warehousing and computing of large amounts of data, returns results within milliseconds or seconds, and then conveniently and flexibly creates reports. This scenario supports a wide range of visual business intelligence (BI) tools. This makes it easy for developers to use business intelligence reports and lowers the threshold for enterprises to implement digital construction.

The following benefits are provided in this scenario:

Access Realtime Compute in real time
This scenario writes tens of thousands to millions of records per second. Real-time updates are visible in real time. Report queries can respond within milliseconds or seconds.
Highly compatible with the BI ecosystem
This scenario is highly compatible with MySQL and SQL:2003 syntax standards, and supports dozens of mainstream BI tools, such as Tableau, FineReport, and Quick BI.

Multi-source joint analysis

This scenario must configure data synchronization links for enterprises to build data warehouses in the cloud, and analyzes the complexity of data caused by sharding. This allows you to focus more on the business logic.

The following benefits are provided in this scenario:

Access of multiple data sources
You can import data from databases such as ApsaraDB RDS, PolarDB-X, PolarDB, Oracle, and SQL Server, big data such as Flink, Hadoop, E-MapReduce (EMR), and MaxCompute, Object Storage Service (OSS), log data such as Kafka and Log Service, and on-premises data.
Warehouses created with a single click
You can quickly synchronize the data from ApsaraDB RDS, PolarDB for MySQL, or a logstore in Log Service to an AnalyticDB for MySQL cluster by using configurations. This scenario allows you to aggregate data from sharding of AnalyticDB for MySQL to the same table to analyze global data.

Interactive query

This scenario requires real-time BI reports and custom multi-dimensional queries. This scenario provides smooth responses and great interactive experiences. If you want to choose the analysis dimension, you do not need to model and pre-calculate, which facilitates exploratory analysis.

The following benefits are provided in this scenario:

Fast query
This scenario can return the related results within milliseconds or seconds. Applications are smooth without stucks. You can have a good experience.
Complex SQL statements supported
This scenario supports queries based on the combination of hundreds of dimensions, and complex join queries of data in dozens of tables and thousands of rows of SQL statements.