Application Scenarios

Provide users with one-stop OLTP (Online Transactional Processing), OLAP (Online Analytical Processing), and HTAP solutions. TiDB is suitable for various application scenarios with high availability, high requirements for strong consistency, and large data scale.

Scenarios with high requirements for data consistency, high reliability, system availability, scalability, and disaster recovery attributes of the financial industry

As we all know, the financial industry has high requirements for data consistency, high reliability, system availability, scalability, and disaster recovery. The traditional solution is to provide services from two data centers within the same city and to provide disaster recovery capacity from a remote data center without providing services. This solution has the following shortcomings: low resource utilization, high maintenance costs, and the RTO (Recovery Time Objective) and RPO (Recovery Point Objective) can’t truly meet the enterprise’s expectations. TiDB uses multiple copies + Multi-Raft protocol to schedule data to different data centers, racks, and machines. When some machines fail, the system can automatically switch, ensuring the system’s RTO <= 30s and RPO = 0.

Scenarios with high storage capacity, scalability, and concurrency requirements for massive data and high concurrency OLTP

With the high-speed development of the business, the data is growing explosively. The traditional single-machine database can’t meet the capacity requirements of the database due to explosive data growth. The feasible solution is to use sharding middleware products or NewSQL database replacements, or use high-end storage devices, among which the most cost-effective solution is the NewSQL database, such as TiDB. TiDB uses a compute-storage separation architecture, which can scale up and down the compute and storage separately. The compute supports up to 512 nodes, each node supports up to 1000 concurrent connections, and the cluster capacity supports up to PB level.

Real-time HTAP scenarios

With the rapid development of 5G, IoT, and AI, enterprises will produce more and more data, possibly reaching hundreds of TB or even PB levels. The traditional solution is to process online transaction business through OLTP databases and synchronize the data to OLAP databases for data analysis through ETL tools. This processing solution has high storage costs and poor real-time performance. TiDB introduces the column storage engine TiFlash and the row storage engine TiKV in version 4.0 to build a true HTAP database. With a slight increase in storage costs, online transaction processing and real-time data analysis can be done in the same system, greatly saving the cost of enterprises.

Scenarios for data aggregation and secondary processing

At present, most enterprises’ business data is scattered in different systems, and there is no unified summary. With the development of the business, the decision-making layer of the enterprise needs to understand the business situation of the entire company in order to make timely decisions. Therefore, it is necessary to aggregate the data scattered in various systems in the same system and carry out secondary processing to generate T+0 or T+1 reports. The traditional common solution is to use ETL + Hadoop to complete, but the Hadoop system is too complicated, and the operation and maintenance and storage costs are too high to meet the user’s needs. Compared with Hadoop, TiDB is much simpler. Businesses can synchronize data to TiDB through ETL tools or TiDB’s synchronization tools, and can directly generate reports in TiDB through SQL.

Truly financial-grade high availability

Compared with the traditional master-slave (M-S) replication scheme, the Raft-based majority election protocol can provide financial-level 100% data strong consistency guarantee, and can achieve fault automatic recovery (auto-failover) without losing a majority of copies, without the need for manual intervention.