solution has the disadvantages of low resource utilization, high maintenance cost, and the fact that RTO (Recovery Time Objective) and RPO (Recovery Point Objective) cannot meet expectations. TiDB uses multiple and machines. When some machines fail, the system can automatically switch to ensure that the system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios with high requirements for one TiKV can reach 9 MiB/s, which is 50% faster than before. The restore speed is scalable and the RTO in DR scenarios is reduced greatly. The RPO in DR scenarios can be as short as 5 minutes. In normal

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.4.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery business can tolerate in a disaster. The following figure illustrates these two concepts: Figure 112: RTO and RPO • Error tolerance objective: Because a disaster can affect different regions. In this doc-

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.4.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery business can tolerate in a disaster. The following figure illustrates these two concepts: Figure 112: RTO and RPO • Error tolerance objective: Because a disaster can affect different regions. In this doc-

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.4.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery business can tolerate in a disaster. The following figure illustrates these two concepts: Figure 112: RTO and RPO 932 • Error tolerance objective: Because a disaster can affect different regions. In this

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.4.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery business can tolerate in a disaster. The following figure illustrates these two concepts: Figure 112: RTO and RPO 940 • Error tolerance objective: Because a disaster can affect different regions. In this

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.4.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery business can tolerate in a disaster. The following figure illustrates these two concepts: Figure 112: RTO and RPO 968 • Error tolerance objective: Because a disaster can affect different regions. In this

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases capabilities: • Replicating incremental data between TiDB clusters with second-level RPO and minute-level RTO. • Bidirectional replication between TiDB clusters, allowing the creation of a multi-active TiDB solution normally before the crash, and the replication lag is small. It allows data loss of 10s at most, that is, RTO <= 5 min, and P95 RPO <= 10s. TiCDC replication lag increases in the following scenarios: • The TPS

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.5.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery can tolerate in a disaster. 987 The following figure illustrates these two concepts: Figure 114: RTO and RPO • Error tolerance objective: Because a disaster can affect different regions. In this doc-

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.5.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery can tolerate in a disaster. 992 The following figure illustrates these two concepts: Figure 114: RTO and RPO • Error tolerance objective: Because a disaster can affect different regions. In this doc-

Multi-Raft protocol to schedule data to different data centers, racks, and machines, ensuring system RTO ￿ 30 seconds and RPO = 0. • Massive data and high concurrency scenarios Traditional standalone databases Describes the DR solutions provided by TiDB. • Compares these DR solutions. 8.5.1.1 Basic concepts • RTO (Recovery Time Objective): The time required for the system to recover from a disaster. • RPO (Recovery can tolerate in a disaster. The following figure illustrates these two concepts: 1072 Figure 115: RTO and RPO • Error tolerance objective: Because a disaster can affect different regions. In this doc-