geographic location and number of replicas as needed. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft performance of TiDB v5.4 in the MPP mode with that of Greenplum and Apache Spark, two mainstream analytics engines, in their latest versions. The test result shows that the performance of TiDB v5.4 in the MPP mode 10000000000000 Set session variables with the following SQL statements: set @@tidb_isolation_read_engines='tiflash'; set @@tidb_allow_mpp=1; set @@tidb_mem_quota_query = 10 << 30; All TPC-H test tables

geographic location and number of replicas as needed. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft performance of TiDB v5.1 in the MPP mode with that of Greenplum and Apache Spark, two mainstream analytics engines, in their 59 latest versions. The test result shows that the performance of TiDB v5.1 in the MPP 10000000000000 Set session variables with the following SQL statements: set @@tidb_isolation_read_engines='tiflash'; set @@tidb_allow_mpp=1; set @@tidb_mem_quota_query = 10 << 30; 60 All TPC-H test tables

geographic location and number of replicas as needed. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft improve the observability of database performance • Continue optimizing the storage and computing engines to improve the system perfor- mance and stability • Reduce the write latency of TiKV by separating performance of TiDB v5.3 in the MPP mode with that of Greenplum and Apache Spark, two mainstream analytics engines, in their latest versions. The test result shows that the performance of TiDB v5.3 in the MPP mode

geographic location and number of replicas as needed. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft performance of TiDB v5.2 in the MPP mode with that of Greenplum and Apache Spark, two mainstream analytics engines, in their 58 latest versions. The test result shows that the performance of TiDB v5.2 in the MPP 10000000000000 Set session variables with the following SQL statements: set @@tidb_isolation_read_engines='tiflash'; set @@tidb_allow_mpp=1; set @@tidb_mem_quota_query = 10 << 30; 59 All TPC-H test tables

geographic location and number of replicas as needed. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft the national character set. 2.6.2.12 Storage engines For compatibility reasons, TiDB supports the syntax to create tables with alternative storage engines. In implementation, TiDB describes the metadata restart 6. Create and start the cluster: Edit the configuration file according to the following template, and name it as topo. �→ yaml: # # Global variables are applied to all deployments and used as

geographic location and number of replicas as needed. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft the national character set. 2.4.2.12 Storage engines For compatibility reasons, TiDB supports the syntax to create tables with alternative storage engines. In implementation, TiDB describes the metadata restart 6. Create and start the cluster: Edit the configuration file according to the following template, and name it as topo. �→ yaml: # # Global variables are applied to all deployments and used as

needed to meet different disaster tolerance levels. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft chunks #42620 @lichunzhu • Fix the issue that TiDB Dumpling might panic when --output-file- �→ template is incorrectly set #42391 @lichunzhu • TiDB Binlog • Fix the issue that an error might occur when the table as the national character set. 100 2.4.2.12 Storage engines TiDB allows for tables to be created with alternative storage engines. Despite this, the metadata as described by TiDB is for the InnoDB

needed to meet different disaster tolerance levels. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft in the table as the national character set. 2.4.2.12 Storage engines TiDB allows for tables to be created with alternative storage engines. Despite this, the metadata as described by TiDB is for the InnoDB restart 6. Create and start the cluster: Edit the configuration file according to the following template, and name it as topo. �→ yaml: # # Global variables are applied to all deployments and used as

needed to meet different disaster tolerance levels. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft in the table as the national character set. 2.4.2.12 Storage engines TiDB allows for tables to be created with alternative storage engines. Despite this, the metadata as described by TiDB is for the InnoDB restart 6. Create and start the cluster: Edit the configuration file according to the following template, and name it as topo. �→ yaml: 94 # # Global variables are applied to all deployments and used

needed to meet different disaster tolerance levels. • Real-time HTAP TiDB provides two storage engines: TiKV, a row-based storage engine, and TiFlash, a columnar storage engine. TiFlash uses the Multi-Raft in the table as the national character set. 2.4.2.12 Storage engines TiDB allows for tables to be created with alternative storage engines. Despite this, the metadata as described by TiDB is for the InnoDB restart 6. Create and start the cluster: Edit the configuration file according to the following template, and name it as topo. �→ yaml: 97 # # Global variables are applied to all deployments and used