AnalyticDB for MySQL is a fully managed data warehouse service that can process petabytes of data in real time. AnalyticDB for MySQL is highly compatible with MySQL and can update data within milliseconds and respond to queries within sub-seconds.
AnalyticDB for MySQL utilizes a data lakehouse architecture to process structured, semi-structured, and unstructured data from data warehouses and data lakes in an efficient manner and build a comprehensive data analysis platform for enterprises. AnalyticDB for MySQL supports batch processing of large amounts of data to meet deep insight requirements and provides high-performance, real-time data analysis capabilities to help enterprises quickly respond to business changes, reduce costs, and improve efficiency.
AnalyticDB for MySQL Enterprise Edition integrates the advantages of multiple earlier editions. Enterprise Edition utilizes a storage-compute coupled architecture for reserved resources to ensure query performance. To handle scenarios that involve periodic or sudden changes in business workloads, Enterprise Edition allows you to scale computing resources based on your business requirements. For more information about the architecture of AnalyticDB for MySQL, see Overall architecture.
What AnalyticDB for MySQL can do for you
Building of enterprise-class data lakehouses
AnalyticDB for MySQL consists of multiple editions. Data Lakehouse Edition and Enterprise Edition are built on a data lakehouse architecture, which simplifies data structures and reduces system complexity and maintenance costs. All data is stored on a centralized platform to ensure data consistency. You can perform batch processing and real-time analysis based on one copy of data.
ETL and data engineering
AnalyticDB for MySQL utilizes local memory, local SSDs, and a global remote distributed cache to accelerate high-performance processing of lakehouse data. This allows AnalyticDB for MySQL to handle real-time analysis scenarios in which queries require responses within hundreds of milliseconds and high-throughput extract, transform, load (ETL) operations that involve hundreds of terabytes of data. AnalyticDB for MySQL integrates the XIHE and Spark engines, provides the zero-ETL feature to allow you to synchronize data from ApsaraDB RDS and PolarDB, and supports various ETL tools, such as Kettle and Scriptella. In addition, AnalyticDB for MySQL supports materialized views and multiple scheduling tools, such as Data Management (DMS), DataWorks, Airflow, DolphinScheduler, and Azkaban. This simplifies the ETL operations and improves query performance.
Data analysis and business intelligence (BI)
AnalyticDB for MySQL is highly compatible with MySQL, provides an SQL editor, and supports various client tools, such as DMS, Navicat, DBeaver, and SQL WorkBench/J. This allows MySQL users to quickly get started with AnalyticDB for MySQL for data query and analysis. AnalyticDB for MySQL provides various analysis functions, such as roaring bitmap functions, funnel and retention functions, and path analysis functions, to help you efficiently perform complex business analysis jobs. AnalyticDB for MySQL also supports mainstream BI tools, such as Quick BI, Power BI, Superset, Metabase, and Tableau, to help you generate reports and dashboards to accelerate data-driven business decision-making.
AnalyticDB for MySQL integrates the Spark engine to provide enhanced data processing capabilities. You can use the Spark editor in the AnalyticDB for MySQL console to submit and manage Spark jobs. You can also use Notebook, spark-submit, PySpark, SDK for Java, and SDK for Python to perform batch processing or stream processing jobs. The Spark engine provides flexible data processing methods and ensures high performance and high availability on large-scale data to meet complex data analysis requirements.
Real-time data analysis
AnalyticDB for MySQL allows you to synchronize data from ApsaraMQ for Kafka and Simple Log Service (SLS) in real time and provides the zero-ETL feature to allow you to obtain data changes from ApsaraDB RDS and PolarDB in near real time without the need to build complex data pipelines. This simplifies the data integration process and ensures data timeliness and consistency. In addition, AnalyticDB for MySQL integrates Spark Streaming to process streaming data and incremental data in an efficient manner. This helps meet real-time data analysis requirements and provides timely and accurate data insights.
User roles and resources
The following table describes the tutorials for different user roles.
Database administrator | Data development engineer | Data analyst | Algorithm engineer |
Database administrator | Data development engineer | Data analyst | Algorithm engineer |
|
|
|
|
