AISWare AIDB is a general-purpose, highly available and high-powered native distributed relational database for enterprises, which has been meticulously built for industries such as telecommunications, government affairs, energy, finance, and transportation based on technologies accumulated over years. The product adopts a native distributed architecture to achieve online flexible scaling and distributed strong consistency, being compatible with the MySQL protocol and supporting 95% of SQL 2016 standards. It has the characteristics of extreme performance and intelligent visual operations. It can exponentially increase the throughput and support millions of concurrent connections, helping customers easily achieve PB-level data management. It has been comprehensively adapted to domestic software and hardware such as Kunpeng/Phytium/UnionTech, providing high-quality options for various industries in the procurement of independent controllable projects.

Product superiority

Product value


“Remote multi-center” deployment

  • Ensuring strong consistency and high reliability of financial data
  • Supporting emergency switching of primary and backup resources for disaster tolerance within seconds
  • Significantly improved safety

OLTP applications

  • Suitable for 100+ industry application scenarios
  • Adopting vertical splitting to form a multi-database system
  • Tiered storage model better balances performance and cost

Batch processing scenario

  • Powerful SQL execution capability and distributed processing capability
  • Completing a large number of business processing in the manner of high throughput and low latency
  • Balancing high-concurrency data service and fast query

Flexible expansion demand

  • Meeting the horizontal expansion demand of large volumes of business
  • The underlying database can be flexibly expanded with the upper application
  • Supporting automatic expansion and reduction under non-stop service

Application scenario

Core system of telecom industry
  • High concurrency and high throughput
  • Million class tpmC
  • Performance improved by 8.5 times
Online trading system of E-commerce
  • Automated expansion and reduction
  • High performance, low cost
  • Friendly and transparent to application development
Financial online trading system
  • Strong consistency guarantee
  • Extreme performance, high availability
  • Fast and automatic recovery of instance failures
Real-time securities market system
  • Fully compatible with MySQL
  • Zero transaction data loss
  • Concurrent access to multiple locations and multiple cities

Customer success case

AISWare AIDB helps a core accounting center in the telecom industry of a province to achieve distributed deployment

The original traditional database of the core accounting center has been replaced, and AIDB native distributed architecture and full-memory storage mode have been adopted, greatly improving the efficiency of daily production links such as data reading and writing and batch operations. Efficient horizontal expansion capabilities have realized the flexible expansion demands of the underlying database depending on upper applications. Under the same hardware facilities, the throughput QPS of the system has increased by more than 5 times, which can meet customers’ demands for PB-level data management and demands for business with high concurrency, high throughput and highly availability.

  • 100w Maximum number of concurrent connection
  • 5+ Increase multiple of throughput
Application case of multi-province billing system

A large enterprise has deployed a billing system in more than 400 cities in more than 30 provinces across the country. High performance under high concurrency has been achieved by optimizing key technologies such as indexing and MVCC, which can meet the requirements of efficient real-time query among massive data. The total time for billing has been increased from the original 17 hours to less than 2 hours, the billing efficiency has been increased by 8.5 times, and manual intervention is no longer required in the process. At the same time, the needs of efficient real-time query and high-performance OLTP business scenarios are met.

  • 8.5 times Performance improved

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