AnalyticDB MySQL is a real-time warehouse built based on the integrated architecture of lakes and warehouses. It is highly compatible with MySQL, with millisecond update and sub second query.Whether unstructured/semi-structured data in the data lake or structured data in the database, AnalyticDB MySQL can be used to simultaneously complete high throughput offline processing and high-performance online analysis, truly achieving the scale of the data lake and the experience of the database.Help enterprises build a data analysis platform to reduce costs and increase efficiency.
——Create one-stop real-time lake warehouse, which can replace CDH/TDH/open source self built/cloud service Spark/Hive/Presto, etc
Product advantages
PB level cloud native real-time warehouse, highly compatible with MySQL, millisecond level update, sub second level query, breaking the isolated island of the warehouse, the scale of the data lake, and the experience of the database.
One data supports both offline processing and online analysis to solve data consistency and timeliness problems;And through the cloud disk multi copy mechanism, data reliability assurance is achieved
It supports setting elastic capacity expansion rules for computing resources on an hourly basis to solve the peak and valley demand of computing resources and reduce the cost of computing resources.
Daily query business peak
During the peak working hours in the daytime, computing resources are popped up on time to make business queries faster and improve the application experience.
Evening ETL calculation peak
At the peak of ETL in the evening, computing resources will pop up on time, allowing ETL computing tasks to run stably. At the low peak, computing resources will be released on time, reducing resource costs.
Hot and cold data layering
Support that data can be divided into hot data and cold data at the table and partition levels. The hot data is stored in high-performance media to speed up query and calculation;Cold data is stored on inexpensive HDD media, saving storage costs.
Cold and hot data setting
In the statement of creating a table, set the cold and hot attributes of the table and partition, and write the data to the corresponding media.
Cold and hot data switching
The cold and hot properties of tables and partitions can be modified at any time, and the system automatically moves data.
Resource group isolation
Support the grouping and isolation of computing resources, so that important and stable computing tasks are not affected by temporary and abnormal tasks, and ensure the stable operation of the business.
Important Task Resource Group
According to the importance of computing tasks or business scope, establish multiple resource groups, allocate computing resources, and assign important tasks to each resource group. Resources are isolated from each other, do not affect each other, and operate stably.
Temporary Task Resource Group
Put the temporary query and development tasks that have not passed the actual data pressure test into the temporary task resource group to avoid affecting the stability of production tasks.
One click warehouse creation
The data in a log database in RDS, PolarDB or log service can be quickly synchronized to the cloud native data warehouse AnalyticDB MySQL cluster through simple configuration steps.
Database data access
Configure DTS synchronization links for multiple database instances of RDS and PolarDB in one click.
Log data access
Configure the SLS data synchronization link to quickly access the log data.
E-commerce: real-time optimization of supply chain
Internet of Things: real-time query of terminal information
Advertising: real-time monitoring of delivery effect
General: BI report analysis acceleration
Detailed operational data to help optimize marketing and product experience
The rise in traffic costs has made users more mature, forcing customers to carry out more refined marketing and provide higher quality products.ADB MySQL provides unified online query and offline computing capabilities, simplifies data architecture, and responds to massive data complex queries in seconds, providing data support for marketing decisions and product optimization.
Capable of providing
Comprehensive and refined operation indicators
It supports the analysis of user behavior, channel transformation, product activity and other refined operational indicators to help customers more efficiently master the product operation status.
Optimize user experience
Detailed analysis of user behavior through ADB MySQL storage intensive instances effectively supports the analysis of product improvement experience and provides a better product experience.
Safe and reliable
Service second level recovery, deployment within/across AZ (Available Zone), automatic fault detection, removal, and replica replay.Three copies of data storage, scheduled full and incremental backups provide financial level data reliability assurance.
Billion level data reading and writing, resource elasticity rising and falling
The e-commerce and marketing SAAS platform scenarios have the characteristics of massive data, promoting the peak change of activity business.ADB MySQL provides powerful batch processing and multi-dimensional complex analysis capabilities, supports customers with multiple functions, including ETL, CRM and online reports, and provides strong analysis support for e-commerce scenario orders, warehousing, distribution, collaborative supply chain and other functions, so as to calmly respond to large-scale activities.
Capable of providing
Support complex SQL
It supports hundreds of thousands of dimension arbitrary combination queries, and supports tens of tables and thousands of rows of SQL complex association queries.
Offline integration
It supports real-time data addition, deletion and modification, integrates online analysis and ETL calculation, and realizes the integration of big data and database.Through resource group isolation, offline computing tasks do not affect each other, ensuring stable business operation.
Calculate storage resource elasticity
The computing and storage separation architecture is adopted to support time-sharing flexibility, realize the elastic expansion of computing resources set by the hour, solve the peak and valley demand of computing resources, and more refined resource utilization and lower cost investment.
The query efficiency has been improved several times, and the comprehensive cost has been greatly reduced
In the IoT scenario, a large number of terminal devices need to be monitored, connected and interacted. Massive data needs to be written and queried in real time, but it is difficult for customers to improve performance and capacity through horizontal expansion of the original traditional database architecture.ADB MySQL is ready to use out of the box. It can quickly carry out business through simple deployment, improve query efficiency and significantly reduce deployment and use costs.
Capable of providing
Elastic lifting configuration
The architecture of separating storage and computing is adopted, which supports the adjustment of the number of nodes and the dynamic upgrade and configuration of instance specifications at any time, and flexibly responds to the changes in business peaks.
Real time warehousing of data
The business data is synchronized to ADB MySQL in real time through data transmission DTS, and the information of each device terminal is monitored in real time. For example, in the smart transportation scenario, the operation efficiency of the transportation system is improved and the travel mode is optimized.
Improvement of operation efficiency
Through the intelligent business analysis system, real-time business data can be quickly obtained to realize the ad hoc analysis and query of massive data, fully tap the value of data, and support more efficient business decisions.
Precision marketing of business and timely feedback of results
In this scenario, customers need to reduce the storage cost of massive historical orders and monitoring data, and ensure the timeliness of marketing effect data.ADB MySQL supports the separation of hot and cold storage data, which can balance the performance and cost at the table level.At the same time, it supports real-time statistical data, monitors the growth, activity and retention of users in different channels, and enables enterprises to quickly analyze the return on investment, so as to improve product experience, optimize marketing programs, and improve overall earnings.
Capable of providing
Hot and cold data layering
Support that data can be divided into hot data and cold data at the table and partition levels. The hot data is stored in high-performance media to speed up query and calculation;Cold data is stored on inexpensive HDD media, saving storage costs.
Real time feedback of marketing effect
Fast query speed, support real-time complex correlation calculation of massive log data and business, improve the timeliness of marketing effect feedback, and quickly adjust the launch strategy.
Real time multi-source data synchronization
It supports multi business data sources and real-time synchronization of structured and unstructured data.
Highly compatible with a variety of BI tools, out of the box
This scenario requires supporting real-time warehousing and calculation of massive data, and returning results at the millisecond/second level to facilitate the free and flexible rapid construction of reports.ADB MySQL supports rich visual BI tools, which are easy for developers to use and lower the threshold of enterprise data construction.
Capable of providing
Highly compatible with BI ecology
It is highly compatible with MySQL protocol and SQL-2003 syntax standard, and supports dozens of mainstream BI tools such as Tableau, Fansoft and QuickBI.
Support multiple data source access
It supports database (RDS, PolarDB-X, PolarDB, Oracle, SQL Server, etc.), big data (Flink, Hadoop, EMR, MaxCompute), OSS, log data (Kafka, SLS, etc.), and local data import.
Easy to use
One click warehouse creation is supported. Data in a log database in RDS, PolarDB MySQL, or log service can be quickly synchronized to the ADB cluster through simple configuration steps.It supports aggregating the data of MySQL databases and tables into the same table, and provides global data analysis capabilities.
It is suitable for Spark offline development scenarios. Only elastic resources are used, and you don't need to keep reserved resources to find documents, picture files @ messages, more cool applications
