TiDB Application Scenarios

This topic has been translated from a Chinese forum by GPT and might contain errors.

Original topic: TiDB 应用场景

| username: xianjuke

For scenarios with high requirements for data consistency, high reliability, system high availability, scalability, and disaster recovery in the financial industry: The financial industry has high requirements for data consistency, high reliability, system high availability, scalability, and disaster recovery. The traditional solution is to provide services from two data centers in the same city and one data center in a different location for data disaster recovery but not for services. This solution has the following drawbacks: low resource utilization, high maintenance costs, and RTO (Recovery Time Objective) and RPO (Recovery Point Objective) that cannot truly meet the enterprise’s expected values. TiDB uses a multi-replica + Multi-Raft protocol to schedule data to different data centers, racks, and machines. When some machines fail, the system can automatically switch to ensure that the system’s RTO <= 30s and RPO = 0.

For OLTP scenarios with high requirements for storage capacity, scalability, and concurrency: With the rapid development of business, data is growing explosively. Traditional single-machine databases cannot meet the capacity requirements of databases due to explosive data growth. Feasible solutions include using middleware products for database and table partitioning or replacing them with NewSQL databases, and using high-end storage devices. Among these, the most cost-effective solution is NewSQL databases, such as TiDB. TiDB adopts a compute-storage separation architecture, allowing independent scaling of compute and storage. It supports up to 512 compute nodes, each node supporting up to 1000 concurrent connections, and the cluster capacity can support PB-level data.

Real-time HTAP scenarios: With the rapid development of 5G, IoT, and AI, the data produced by enterprises will increase, potentially reaching hundreds of TB or even PB levels. The traditional solution is to handle online transaction processing (OLTP) with an OLTP database and synchronize data to an OLAP database for analysis using ETL tools. This solution has high storage costs and poor real-time performance. TiDB introduced the columnar storage engine TiFlash in version 4.0, combined with the row storage engine TiKV, to build a true HTAP database. This allows online transaction processing and real-time data analysis within the same system with minimal additional storage costs, greatly saving enterprise costs.

Data aggregation and secondary processing scenarios: Currently, most enterprises’ business data is scattered across different systems without a unified aggregation. As business develops, decision-makers need to understand the overall business situation of the company to make timely decisions. Therefore, it is necessary to aggregate data scattered across various systems into one system and perform secondary processing to generate T+0 or T+1 reports. The traditional common solution is to use ETL + Hadoop, but the Hadoop system is too complex, and the maintenance and storage costs are too high to meet user needs. Compared to Hadoop, TiDB is much simpler. Businesses can use ETL tools or TiDB’s synchronization tools to synchronize data to TiDB, and reports can be directly generated in TiDB using SQL.

About PingCAP

Founded in 2015, PingCAP is an enterprise-level open-source distributed database vendor that provides open-source distributed database products, solutions and consulting, technical support, and training certification services. It is committed to providing stable, efficient, secure, reliable, and open-compatible new data service platforms for global industry users, liberating enterprise productivity, and accelerating digital transformation and upgrading. TiDB, as a general-purpose distributed database, has been used in online production environments by over 1500 enterprises worldwide, including Bank of China, China Everbright Bank, Shanghai Pudong Development Bank, Zhejiang Commercial Bank, Beijing Bank, WeBank, Yillion Bank, Baixin Bank, China UnionPay, China Life, Ping An Life, Ping An Property & Casualty, Guotai Junan Securities, Huatai Securities, Lufax, Mashang Consumer Finance, Lakala, China Mobile, China Unicom, China Telecom, Xinhua Finance, People’s Online, Jilin Xiangyun, Zhongti JunCai, State Grid, ENN Energy, Peking University People’s Hospital, Beijing Friendship Hospital, Gree Electric, Li Auto, XPeng Motors, VIVO, OPPO, McDonald’s, Yum China, China Post, SF Express, ZTO Express, Tencent, Meituan, JD.com, Pinduoduo, Xiaomi, Sina Weibo, 58.com, 360, Zhihu, iQIYI, Bilibili, Ximalaya, New Oriental, PalFish, Xiaohongshu, Autohome, NetEase Games, Gaia Interactive, Youzu Interactive, Square (USA), PayPay (Japan), Dailymotion (France), Shopee (Singapore), ZaloPay (Vietnam), BookMyShow (India), and more, covering industries such as finance, telecommunications, energy, public utilities, high-end manufacturing, high-tech, new retail, logistics, internet, gaming, and more.