data silos or integration bottlenecks. A modern Real-Time UDL typically includes: Real-time data ingestion from structured, semi-structured and unstructured sources (IoT, logs, event streams). Multi-model real- time insights, delaying critical business actions. Optimized Ingestion, Indexing and Querying Real-Time UDLs index data upon ingestion and execute complex queries on very large data sets in the sub-second for many applications. Continuous data flow: CrateDB handles high-throughput, high-velocity data ingestion and analysis, ensuring businesses can respond dynamically to changing conditions. Instant data insights:

test input.18 Aurora Innovation Higher-level tests in practice Safely rewriting a critical data ingestion pipeline 500,000 + lines of code 12,000 + real-world datasets 10,000 + attributes to verify messages:[MessageBuffer]; } root_type Messages;52 Aurora Innovation Data ingestion w/ async processing53 Aurora Innovation Data ingestion w/ on-demand processing54 Aurora Innovation Data Retention Local Filesystem

Network Training C++ Application Code SYCL in Embedded Systems, Automotive, and AI Compilation Ingestion FPGA DSP Dedicated Hardware GPU Vision / Inferencing Engine Compiled Code Hardware Acceleration

cleaning up stale regions might accidentally delete valid data #17258 @hbisheng • Fix the issue that Ingestion picked level and Compaction Job Size(files) are displayed incorrectly in the TiKV dashboard in TiDB Bin- log 6 Deprecated Y Y Y Y Y Y Y Y Y Y Change data cap- ture (CDC) Y Y Y Y Y Y Y Y Y Y Y Stream data to Ama- zon S3, GCS, Azure Blob Stor- age, and NFS through TiCDC Y Y Y Y Y E N N N N N transactions different processing engines based on the specific business. • Real-time stream processing When using TiDB in real-time stream processing scenarios, TiDB ensures that all the data flowed in constantly

TiCDC and PITR. 94 Data im- port and ex- port 8.4 8.3 8.2 8.1 7.5 7.1 6.5 6.1 5.4 5.3 5.2 5.1 Stream data to Ama- zon S3, GCS, Azure Blob Stor- age, and NFS through TiCDC Y Y Y Y Y Y E N N N N N TiCDC different processing engines based on the specific business. • Real-time stream processing When using TiDB in real-time stream processing scenarios, TiDB ensures that all the data flowed in constantly in the URL. Then, resultset is automatically closed but the result set to be read in the previous stream- ing query is lost. • The second method: Use Cursor Fetch by first setting FetchSize as a positive

rolling back the partition DDL tasks #51090 @jiyfhust • Fix the issue that the value of max_remote_stream is incorrect when executing EXPLAIN ANALYZE #52646 @JaySon-Huang • Fix the issue that querying the Y Y Y Y Y Y TiDB Bin- log 6 Y Y Y Y Y Y Y Y Y Change data cap- ture (CDC) Y Y Y Y Y Y Y Y Y Stream data to Ama- zon S3, GCS, Azure Blob Stor- age, and NFS through TiCDC Y Y Y E N N N N N back the different processing engines based on the specific business. • Real-time stream processing When using TiDB in real-time stream processing scenarios, TiDB ensures that all the data flowed in constantly

Y Y Y Y TiDB Bin- log 6 Y Y Y Y Y Y Y Y Y Y Change data cap- ture (CDC) Y Y Y Y Y Y Y Y Y Y Stream data to Ama- zon S3, GCS, Azure Blob Stor- age, and NFS through TiCDC Y Y Y Y E N N N N N back different processing engines based on the specific business. • Real-time stream processing When using TiDB in real-time stream processing scenarios, TiDB ensures that all the data flowed in constantly in the URL. Then, resultset is automatically closed but the result set to be read in the previous stream- ing query is lost. • To use Cursor Fetch, first set FetchSize as a positive integer and configure

4 Filter DML Events Using SQL Expressions · · · · · · · · · · · · · · · · · · · · · · · · 901 7 Stream Data 903 7.1 TiCDC Overview · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 1195 7.6.8 How can I find out whether a DDL statement fails to execute in down- stream during TiCDC replication? How to resume the replication?· · · · 1196 7.6.9 The Kafka: client has TiCDC and PITR. 99 Data im- port and ex- port 8.4 8.3 8.2 8.1 7.5 7.1 6.5 6.1 5.4 5.3 5.2 5.1 Stream data to Ama- zon S3, GCS, Azure Blob Stor- age, and NFS through TiCDC Y Y Y Y Y Y E N N N N N TiCDC

| | Oracle Enterprise Linux 8 及以上的版本 | x86_64 | | Ubuntu LTS 20.04 及以上的版本 | x86_64 | | CentOS 8 Stream | x86_64 ARM 64 | | Debian 10 (Buster) 及以上的版本 | x86_64 | | Fedora 38 及以上的版本 | x86_64 | | openSUSE Unbreakable Enterprise Kernel。 521 • CentOS Linux 8 的上游支持已于 2021 年 12 月 31 日终止，但 CentOS 将继续提供对 CentOS Stream 8 的支持。 • TiDB 将不再支持 Ubuntu 16.04。强烈建议升级到 Ubuntu 18.04 或更高版本。 • 从 v8.4.0 开始，TiDB 依赖 glibc 2.28。如果 Snowflake 中创建 TiDB 表对应的数据副本 在上一章节，TiDB 的增量变更日志已经被同步到 Snowflake 中，本章节将介绍如何借助 Snowflake 的 TASK 和 STREAM 功能，将实时写入 Snowflake 的数据变更日志根据 INSERT、UPDATE 和 DELETE 等事件类型分别处理，写 入一个与上游 TiDB 结构相同的表中，从而在 Snowflake

64 | | Oracle Enterprise Linux 8 及以上的版本 | x86_64 | | Ubuntu LTS 20.04 及以上的版本 | x86_64 | | CentOS Stream 8 | x86_64 ARM 64 | | Debian 10 (Buster) 及以上的版本 | x86_64 | | Fedora 38 及以上的版本 | x86_64 | | openSUSE 提供的 Unbreakable Enterprise Kernel。 – TiDB 将不再支持 Ubuntu 16.04。强烈建议升级到 Ubuntu 18.04 或更高版本。 – CentOS Stream 8 已于 2024 年 5 月 31 日 End of Builds。 525 • 对于以上两个表格中所列操作系统的 32 位版本，TiDB 在这些 32 位操作系统以及对应的 CPU 架构上不保 Snowflake 中创建 TiDB 表对应的数据副本 在上一章节，TiDB 的增量变更日志已经被同步到 Snowflake 中，本章节将介绍如何借助 Snowflake 的 TASK 和 STREAM 功能，将实时写入 Snowflake 的数据变更日志根据 INSERT、UPDATE 和 DELETE 等事件类型分别处理，写 入一个与上游 TiDB 结构相同的表中，从而在 Snowflake