As corporate IT and Internet systems develop, they produce increasingly more data. The accumulated data volume enables data applications to become independent of business systems, which is a qualitative leap. A growing number of industries such as logistics, transportation, and new retail uses online analytical processing (OLAP) to refine their business operations. They can use OLAP to adjust production guidelines, operation efficiency, and enterprise decisions accordingly.
Typically, business systems use MySQL or PostgreSQL for online transaction processing (OLTP). These relational databases are good at performing transactional processing and support frequent INSERT and UPDATE operations. OLTP systems are inadequate to compute large amounts of data. For example, you need to compute tens of millions of data records or complex computing is required. In this case, you need to use OLAP systems.
Cloud-native for MySQL (formerly known as AnalyticDB for MySQL) is a cloud-based warehouse that can process petabytes of highly concurrent data in real time. It is an OLAP data warehouse. AnalyticDB for MySQL uses relational models to store data and provides SQL statements to compute and analyze data flexibly. No prior data modeling is required. Using the seamless scaling capability of the cloud, ADB for MySQL can compute tens of billions of or more data entries in milliseconds.
ADB RDS for MySQL allows you to use SQL statements to build a relational data warehouse. You can manage databases, scale in or out nodes, and flexibly change specifications. It provides various visualization and ETL tools to simplify data processing for enterprises.
ADB for MySQL is designed to refine business operations, gain an insight into the value of data in real time, and continuously promote the data-based transformation of enterprises.
Why ADB for MySQL
ADB for MySQL is a PB-level data warehouse hosted in the cloud for large-scale parallel processing (MPP). Compared with other data warehouses or OLAP solutions in the industry, analyticdb for MySQL has the following advantages as a SQL Data Warehouse:
ADB for MySQL uses the new generation of an ultra-large scale engine that integrates MPP with directed acyclic graphs (DAGs), and adopts the row-column hybrid storage, automatic indexing, and an intelligent Optimizer to instantly analyze hundreds of billions of data entries in multiple dimensions to quickly discover data value. ADB for MySQL performs complex SQL queries 10 times faster than traditional relational databases. In addition, ADB for MySQL allows you to quickly scale up a cluster to thousands of nodes to further improve the query response speed.
Analyticdb for MySQL provides an extremely flexible architecture that separates storage from computing. You can adjust the number of nodes at any time and dynamically change the instance type. ADB for MySQL also allows you to flexibly switch between SATA nodes that have a large storage capacity and SSD nodes that have high performance. For example, you can increase the number of node groups from eight C4 node groups to 12 C8 node groups, or decrease the number of node groups from 12 C8 node groups to eight C4 node groups. This way, enterprises can flexibly control costs.
As a PB-level SQL data warehouse hosted in the cloud, ADB RDS for MySQL is fully compatible with the MySQL protocol and SQL:2003, and supports standard SQL and common BI tools, and ETL tools. Analyticdb for MySQL is designed to simplify real-time data-based business operations for enterprises.
Analyticdb for MySQL features a fully distributed structure without any single point of failure (SPOF) design. This allows a database instance to dynamically and linearly scale out its nodes to thousands of nodes. After the scale-out, AnalyticDB for MySQL can significantly speed up the response to SQL queries and process more concurrent SQL queries.
- High Concurrency for Fast Writes
AnalyticDB for MySQL supports quick data write and update in real time, high concurrency queries, interactive analytics, and ETL integration. AnalyticDB for MySQL supports real-time data write on an ultra-large scale in compliance with the Raft consensus protocol. For scenarios that require high concurrency and throughput, you can scale out clusters as needed. For example, the disk space can be increased from GB level to hundreds of PB level. Clusters can be scaled to process tens of millions transactions per second.
- High data compression
ADB for MySQL uses hybrid row-column storage technology. Data in different columns has different types and can be compressed using different algorithms. You can choose the most suitable compression algorithm for different columns or even different blocks in the same column. The compression algorithms include encoding and general-purpose compression. More than 10 compression algorithms are used, and the average data compression ratio is about 3 to 10 times.