This topic describes the scenarios for which DRDS is designed.
- Services that require ultra-high concurrency and large-scale data storage for online transactions
- Traditional enterprise-grade applications that require more powerful online transactional databases due to the rapid growth of data
In online transaction processing (OLTP) scenarios, database capacity is typically determined by concurrency, data storage, and the response time of complex SQL queries. If one of these three factors has become a bottleneck, or if you want to prepare for the potential rapid growth of your services, you can use DRDS to create a distributed database. This can reduce future pressure on database expansion and O&M.
In the early stages of service development, you must consider many factors to determine whether to use a centralized or distributed database system. However, the database features required for your service, such as SQL statements, data types, transactions, and indexes, do not change. Most services require databases that have complete support for SQL syntax, data types, transactions, and indexes, and can be scaled out in specific scenarios. For services that are rapidly developing, DRDS is the distributed database solution with the highest level of vitality and continuity.
The following cost-related factors must be considered when you select a database type:
- If the development of new services is too difficult, projects may be delayed and business results may be unsatisfactory. For this reason, new databases must fully support the usage habits and features of existing databases that are commonly used. DRDS is compatible with the MySQL ecosystem, including its mainstream clients, drivers, and SQL syntax. This compatibility enables interconnection and adaptation with your services.
- To support services, databases must provide long-term stability and high performance. DRDS distributes data and load to multiple ApsaraDB RDS for MySQL instances. Therefore, DRDS databases are more stable than large-scale centralized databases when increasing load needs to be processed. In terms of performance, DRDS natively supports distributed processing and can handle ultra-high concurrency. Based on single-instance parallel computing and multi-instance directed acyclic graph (DAG) computing, DRDS can meet the complex computing requirements of most online services.
DRDS partitioning modes can be seamlessly connected to meet the database scalability requirements of each stage of the lifecycle of a service.