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TDSQL Boundless

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Technical Evolution and Usage Practices of Online DDL
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TDSQL Boundless Selection Guide and Practical Tutorial
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Glossary

Kernel Overview

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Terakhir diperbarui: 2026-03-12 10:00:31
The TDSQL Boundless computing engine is highly compatible with MySQL 8.0. At the feature level, users can refer to MySQL 8.0 Official Documentation. For incompatible parts, users may consult MySQL Compatibility.
At the storage level, TDSQL Boundless employs an LSM Tree architecture instead of the B+Tree engine of native MySQL, and has undergone distributed transformation. Therefore, its storage behavior is not entirely equivalent to native MySQL. For a fundamental introduction to the storage and computing engines, users can refer to System Principles.
Building on high compatibility with MySQL 8.0, TDSQL Boundless incorporates numerous extended features, which enables it to better assist users in building applications under massive data scenarios.
Module
Feature
Description
Features
Compared to the traditional MySQL InnoDB engine, TDSQL Boundless provides compression capabilities. This article offers evaluation of disk capacity for users who are planning database migration or selection.
Flashback Read and Standby Read are mechanisms in database systems for reading historical data versions. Users can specify a particular historical point in time or a time interval from the current time to obtain a data snapshot of the database at a specific point in the past.
The Synchronized Table feature allows a table to store consistent replicas across multiple physical nodes, enabling access to this table to be maximally converted into local access and eliminating RPC calls. Synchronized Tables are suitable for read-intensive scenarios with infrequent writes.
Online DDL (Online Data Definition Language) aims to modify database table structures while supporting concurrent read and write operations, reducing the table lock time and ensuring database availability. In distributed environments, DDL operations need to be performed simultaneously across multiple nodes, requiring not only guaranteed safety for concurrent DDL & DML operations but also considerations for performance, execution efficiency, and crash-safe mechanisms.
Distribution Policy (DP) is the rule system governing data object distribution in TDSQL Boundless. By explicitly setting rules for data objects, the Metadata Service (MC) can perform corresponding scheduling. Through configuring different scheduling rules, users gain granular control over data object distribution, including number of replicas, replica location distribution, and Replication Group Leader placement.
TDSQL Boundless extends specialized parallel Hints based on compatibility with MySQL's official Hint standards, tailored for characteristics of distributed parallel execution. These Hints primarily serve as optimizer directives, enabling users to exercise finer-grained control over strategies for parallel execution of queries and enhance the performance of complex queries.
TDSQL Boundless recycle bin feature provides a data security safeguard mechanism. When a user accidentally deletes a table, they can quickly recover data through the recycle bin. The system uses a data dictionary table to store information about deleted database objects (including databases, tables, and so on), supporting data recovery operations.
Performance Features
TDSQL Boundless supports fast data import into databases via bulk load. Compared to traditional SQL transaction-based writes, the bulk load fast import mode typically improves performance by 5~10 times, making it suitable for migrating existing large-scale databases to new TDSQL Boundless clusters during system deployment.
TDSQL Boundless actively aligns SST files with Region boundaries during the data Compaction process. This enables direct identification and transfer of entire files during replica migration, significantly enhancing efficiency.
The Adaptive Hotspot Lock Manager in TDSQL Boundless efficiently supports pessimistic locking on LSM-trees. The lock manager can split along with Regions, effectively dispersing hotspot bottlenecks.

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