This topic describes the core benefits of AnalyticDB for MySQL.
AnalyticDB for MySQL is a cloud native enterprise-grade data warehousing service that integrates database and big data technologies. AnalyticDB for MySQL delivers lightning-fast performance. Data is queryable milliseconds after it is written, and queries can be handled within a second. AnalyticDB for MySQL's unique design lets you aggregate and analyze structured, semi-structured, and unstructured data from data lakes and databases. It is able to perform both high-throughput batch processing and high-performance real-time analysis all in one place, reducing costs and improving efficiency.
High elasticity and extensibility
AnalyticDB for MySQL is built on a cloud native architecture, decoupling storage and computing resources. This lets you scale computing and storage resources individually and on demand, so that you can rightsize your application and solve individual bottlenecks at relatively lower costs.
High performance at low costs
In AnalyticDB for MySQL, data becomes queryable milliseconds after it is written, even in large amounts, and strong data consistency is ensured.
AnalyticDB for MySQL can handle operations on large amounts of data within seconds or milliseconds, delivering a performance for complex queries that is 10 times faster than relational databases.
AnalyticDB for MySQL is highly flexible and allows you to change cluster configurations as your business evolves. You can scale clusters based on a schedule or on demand. In addition, AnalyticDB for MySQL supports tiered storage of hot and cold data. You are billed for the amount of storage space occupied, which significantly reduces computing and storage costs.
Data Lakehouse Edition (V3.0) supports integrated resource scheduling. You can use scheduled scaling and on-demand scaling to rightsize computing resources for data analysis and processing. This increases resource utilization and reduces resource costs.
Data Lakehouse Edition (V3.0) offers a consistent user experience. You can use consistent billing units, metadata, permissions, programming languages, and transmission links to improve development efficiency.
Data Lakehouse Edition (V3.0) uses a standardized interface to implement features of the multi-language programmable Spark compute engine.
The Spark engine is integrated with the computing resources and data storage of AnalyticDB for MySQL. You can use Serverless Spark to perform low-cost batch processing based on on-demand computing resources and write data directly to internal storage for real-time analysis.
Data Lakehouse Edition (V3.0) supports the Hudi framework for cost-effective, near-real-time batch data updates. Data Lakehouse Edition supports the open source Hudi framework to implement near-real-time processing for incremental data and data ingestion based on the low-cost Object Storage Service (OSS).
Ease of use
AnalyticDB for MySQL is highly compatible with MySQL protocols and the SQL:92, SQL:99, and SQL:2003 standards. You can easily get started with it by using standard SQL statements, common BI tools, and extract-transform-load (ETL) tool platforms.