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 replicas and the Multi-Raft 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 storage capacity, scalability supports snapshot checkpoint backup, improves the recovery performance of PITR by 50%, and reduces the RPO in common scenarios to as short as 5 minutes. • Improve the TiCDC throughput of replicating data 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 cannot meet the satisfies the following requirements: • Back up cluster data to a disaster recovery (DR) system with an RPO as short as 5 minutes, reducing data loss in disaster scenarios. • Handle the cases of misoperations last refresh every 3-5 minutes to the backup storage, which can achieve a Recovery Point Objective (RPO) as short as five minutes. 8.3.1.3.2 Restore backup data Corresponding to the backup features, you

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 cannot meet the satisfies the following requirements: • Back up cluster data to a disaster recovery (DR) system with an RPO as short as 5 minutes, reducing data loss in disaster scenarios. • Handle the cases of misoperations last refresh every 3-5 minutes to the backup storage, which can achieve a Recovery Point Objective (RPO) as short as five minutes. 864 8.3.1.3.2 Restore backup data Corresponding to the backup features

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 cannot meet the satisfies the following requirements: • Back up cluster data to a disaster recovery (DR) system with an RPO as short as 5 minutes, reducing data loss in disaster scenarios. 849 • Handle the cases of misoperations last refresh every 3-5 minutes to the backup storage, which can achieve a Recovery Point Objective (RPO) as short as five minutes. 8.3.1.3.2 Restore backup data Corresponding to the backup features, you

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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 cannot meet the satisfies the following requirements: • Back up cluster data to a disaster recovery (DR) system with an RPO as short as 5 minutes, reducing data loss in disaster scenarios. • Handle the cases of misoperations last refresh every 3-5 minutes to the backup storage, which can achieve a Recovery Point Objective (RPO) as short as five minutes. 8.3.1.3.2 Restore backup data Corresponding to the backup features, you

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 cannot meet the satisfies the following requirements: • Back up cluster data to a disaster recovery (DR) system with an RPO as short as 5 minutes, reducing data loss in disaster scenarios. • Handle the cases of misoperations last refresh every 3-5 minutes to the backup storage, which can achieve a Recovery Point Objective (RPO) as short as five minutes. 8.3.1.3.2 Restore backup data Corresponding to the backup features, you

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 cannot meet the following key capabilities: • Replicating incremental data between TiDB clusters with second-level RPO and minute-level RTO. • Bidirectional replication between TiDB clusters, allowing the creation of 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 increases significantly

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 cannot meet the satisfies the following requirements: • Back up cluster data to a disaster recovery (DR) system with an RPO as short as 5 minutes, reducing data loss in disaster scenarios. • Handle the cases of misoperations last refresh every 3-5 minutes to the backup storage, which can achieve a Recovery Point Objective (RPO) as short as five minutes. 904 8.4.1.3.2 Restore backup data Corresponding to the backup features

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 cannot meet the satisfies the following requirements: • Back up cluster data to a disaster recovery (DR) system with an RPO as short as 5 minutes, reducing data loss in disaster scenarios. • Handle the cases of misoperations last refresh every 3-5 minutes to the backup storage, which can achieve a Recovery Point Objective (RPO) as short as five minutes. 908 8.4.1.3.2 Restore backup data Corresponding to the backup features