qData Open-Source Edition Release Notes

v1.6.0 - 2026-07-23

The version qData v1.6.0 is code-named "Ultimate Lightweight Era". This version mainly introduces the DataX lightweight execution engine and a built-in lightweight scheduler, further enhancing the data integration task execution and scheduling capabilities of the open source version. At the same time, adjustments have been made to some interactive protections and log content.

🛠 Main Update Content

1. Execution engine

• Added DataX lightweight execution engine, supporting the use of DataX to execute data integration tasks.
• Introduce a lightweight execution method for data integration tasks to reduce the dependency of task execution on related components.

2. task scheduling

• Added: A built-in lightweight scheduler that supports the scheduling of data integration tasks within the qData system.
• Supports task scheduling and execution by combining the built-in lightweight scheduler with the DataX execution engine.

3. System detail optimization

• Add anti-repeated click processing to system buttons to avoid repeated submission, execution, and saving.
• Supplement the basic anti-misoperation processing for data integration.
• Translate some of the regular log content into English.

📌 Version Summary

qData v1.6.0 has improved the lightweight execution and built-in scheduling capabilities of the open-source version, and made adjustments to the details of data integration operations and log display.

v1.5.4 - 2026-06-25

This release focuses on two major areas: enhanced internationalization capabilities and frontend UI experience optimization. It further improves multilingual adaptation logic and standardizes frontend static resource management. In addition, the login page visual assets and sidebar menu icons have been updated to improve overall page consistency, enhancing the user experience in multilingual scenarios and improving frontend engineering maintainability.

🛠 Major Updates

1. Internationalization Improvements

• Improved full-page multilingual translation adaptation, supporting language switching for page dialogs, operation prompts, form validation messages, and other text content;
• Standardized the i18n language package directory structure to improve the maintainability of language resources;
• Added missing translation entries for business scenarios to fill multilingual text gaps during actual usage.

2. Frontend UI Visual Optimization

• Replaced the login page banner assets and unified visual dimensions and display proportions;
• Updated all sidebar menu function icons, optimizing icon resolution and color adaptation;
• Improved visual consistency across core pages such as the login page and menu bar.

3. Static Resource Engineering Standards

• Adjusted the frontend static resource directory structure and organized resources by type;
• Standardized static resource file naming rules using lowercase words separated by hyphens;
• Improved the clarity of static resource management and reduced future maintenance and extension costs.

📌 Version Summary

v1.5.4 further completes the system’s internationalization capabilities and standardizes frontend static resource management. By updating the login page and sidebar menu visual assets, this release improves page adaptability and overall visual consistency in multilingual scenarios, while also enhancing the standardization and maintainability of frontend engineering resource management.

v1.5.3 - 2026-06-18

This release focuses on multilingual internationalization, fully delivering Chinese, English, and Japanese support across three core carriers: the official website, the product system, and the supporting documentation site. It closes key gaps in multilingual usage, addresses language barriers for overseas developers when accessing, operating, and reading qData materials, and enables community users worldwide to use the qData data platform smoothly. It also strengthens the product's globalization foundation and expands applicable scenarios for the open-source edition.

🛠 Major Updates

1. Full-Scope Multilingual Internationalization

• Adds complete Chinese, English, and Japanese language packs, with one-click system language switching.
• Fully adapts the official website to all three languages, including menus, introductions, and guidance copy.
• Supports multilingual display for all product backend menus, dialogs, prompts, and form fields.
• Builds multilingual branches for the supporting documentation site, providing tutorials and deployment documentation in each language.

📌 Version Summary

v1.5.3 significantly improves international service capabilities and cross-region collaboration efficiency by completing the Chinese, English, and Japanese support system.

v1.5.2 - 2026-05-22

This release focuses on logical model upgrades and data asset upgrades. It redesigns the model creation and publishing flows, supports retrieving metadata lists during data asset registration, and allows assets to be bound to data modeling information.

🛠 Major Updates

1. Logical Model Upgrade

Data Modeling - Logical Model - Create Model (redesign)

• The left category tree is adjusted to two filter dimensions: public layer and application layer.
• Adds four table types: detail table, summary table, dimension table, and application table.
• Supports binding modeling information when creating a model, including warehouse layer, business category, data domain, and topic.
• Supports automatically generating the model's full table name.
• Supports logical model create, edit, delete, and preview operations.

Data Modeling - Logical Model - Publish Model (redesign)

• The left category tree is adjusted to two filter dimensions: public layer and application layer.
• Supports quick filtering by Chinese name, English name, and warehouse layer.
• Adds two publishing modes: delete and rebuild and incremental publishing.
• Supports logical model republishing.

2. Data Asset Upgrade

• Supports tree-based classification maintenance by business category, topic domain, and warehouse layer.
• Supports quick filtering by asset type, asset name, and publishing status.
• Supports register, edit, delete, view, and tag operations for database table assets.
• Supports selecting metadata for database table assets.
• Supports maintaining modeling information such as table type, warehouse layer, business category, data domain, and topic.
• Supports maintaining the asset name and table naming convention for data assets.
• Supports batch setting basic information during database table asset registration, including table type, warehouse layer, business category, data domain, topic, and table naming convention.

📌 Version Summary

qData v1.5.2 improves the connection between logical models and data assets, allowing modeling information to be reused throughout asset registration and maintenance. This further improves data asset management efficiency and strengthens modeling standardization.

v1.4.0 - 2026-05-13

This release introduces the core Metadata Management module. By building a full lifecycle from collection and monitoring to finalized asset versions, it enables automated acquisition and fine-grained control of metadata such as tables, fields, and views.

🛠 Major Updates

1. Core Feature: Metadata Management

Metadata Collection and Instance Monitoring

• Supports creating and maintaining collection tasks with custom task names, descriptions, and owners.
• Supports multiple data source types, specific database instances, and flexible collection ranges, including all databases or specified databases.
• Supports selecting databases on demand and marking source systems.
• Provides an intelligent update strategy that automatically handles metadata additions, changes, and deletions, with manual or scheduled execution by frequency.
• The task list displays data source type, enabled status, latest collection result, and runtime.
• Adds collection instance management to view each run's execution status, data source, and owner information.
• Supports viewing detailed instance run logs for fast troubleshooting.

Latest Metadata (table type)

• Supports browsing pre-release table metadata from a data source perspective through the left tree structure.
• Displays metadata name, description, latest version, and update frequency.
• Supports table-level basic information, such as table comments, database name, and version number, plus field-level details such as field name, data type, nullable status, and default value.
• Introduces version management to record version numbers, change types, change details, and operators.

Finalized Metadata (table type)

• Supports selecting and marking finalized / effective versions from the latest metadata to provide stable and trusted table metadata views.
• Supports viewing finalized table metadata by data source, including basic descriptions and source system information.
• Preserves field information and version change records in the finalized state.

📌 Version Summary

v1.4.0 completes a key part of the metadata management loop. Automated collection solves metadata acquisition problems, latest and finalized views support different data development and asset management scenarios, and version management improves transparency and maintainability.

v1.3.0 - 2026-04-27

This release introduces the standalone qData Intelligent Q&A for Data (ChatBI) module. By introducing Text2SQL, it greatly lowers the barrier for business-side data queries and enables "ask and get". It also provides a transparent, verifiable SQL generation chain for technical teams, improving enterprise data consumption and delivery efficiency.

🛠 Major Updates

1. Core Feature: qData Intelligent Q&A for Data

• Conversational data queries: users can retrieve data directly through natural language conversations without writing complex SQL.
• Flexible analysis configuration: users can define the analysis scope before a conversation, covering data sources, fact tables, and related dimension tables.
• Dimension relationship configuration: related dimension tables support multi-table joins. The system can automatically identify relationships between fact tables and dimension tables, and also supports manual relationship mapping.
• Multimodal result presentation: query results can be shown as tables, bar charts, and other common chart types.
• Q&A mode expansion: provides intelligent Q&A and intelligent charts modes for different analysis scenarios.
• Transparent generation chain: supports viewing the generated Text2SQL statements for logic verification and troubleshooting.
• Flexible result conversion: supports switching among bar charts, detailed data, and Text2SQL.
• Collaboration and traceability: supports one-click result export and historical conversation review.

📌 Version Summary

This release completes the core ChatBI business loop. With qData Intelligent Q&A for Data, business users can perform more self-service analysis, while technical teams can verify and govern the process through a transparent SQL chain.

v1.2.0 - 2026-03-27

This release focuses on reconstructing data modeling capabilities and improving the governance system, fully landing enterprise data warehouse planning and data asset management capabilities.
It adds three core modeling capabilities: data warehouse layer management, data domain management, and topic domain management. These capabilities provide full-process visual control from warehouse architecture design and business domain division to topic domain aggregation. It also presets standardized development menus for Data Governance - Metadata Management, connecting metadata collection, viewing, and basic management flows, and completing the governance module foundation.

🛠 Major Updates

1️⃣ Core Feature Expansion

• The data modeling module adds data warehouse layer management: supports standard layers such as ODS, DWD, DWS, ADS, and DIM, and uniformly maintains layered table-building rules.
• The data modeling module adds data domain management: classifies data by business process or business object, supports unified management of names, codes, and descriptions, and provides standardized data boundaries for model design.
• The data modeling module adds topic domain management: manages business topic aggregation under data domains, maintains names, codes, descriptions, and other information, and provides a clear topic perspective for model construction and data integration.
• The Data Governance module provides a preset metadata management menu: includes core development menus such as metadata collection, metadata query, metadata details, and metadata catalog, improving the basic capabilities of the governance module.

2️⃣ Performance and Experience Optimization

• Data Integration and Data Development list optimization

  • Before optimization: lists had too many columns, pages often exceeded screen width, users had to scroll horizontally to view full information, related information was scattered, items were easy to miss, and browsing efficiency was low.
  • Optimization approach: use a combined display method, arranging related fields vertically in the same column, such as merging runtime status and schedule status display, to reduce horizontal space usage.
  • After optimization: key information is visible on one screen without horizontal scrolling, related information is displayed together, the interface is cleaner and more intuitive, and query and operation efficiency are significantly improved.

• Deep performance optimization for Data Integration / Data Development list APIs, with faster loading, more stable filtering, and much smoother performance in large-list scenarios.

📌 Version Summary

This release focuses on completing core data modeling capabilities, enabling full-dimensional management of warehouse layers, data domains, and topic domains. It also improves the Data Governance - Metadata Management basic menu and builds an integrated capability foundation for "data warehouse modeling + Data Governance". Through feature expansion, experience optimization, and issue fixes, the platform becomes more practical and stable for enterprise data warehouse construction and data asset organization scenarios.

v1.1.2 - 2026-02-12

This update mainly focuses on full Apache Doris data source support, expanded Data Quality audit capabilities, and enhanced Data Integration transformation components, including the following improvements:

• New source support: Adds Apache Doris data source support and implements unified access and usage across multiple core modules.
• Rule enhancement: Expands Data Quality audit rules to cover more real business validation scenarios.
• Component enhancement: Adds multiple transformation components to Data Integration tasks to improve data processing flexibility.
• Issue fixes: Fixes several known issues reported by the community, improving platform stability and user experience.

✨ Major Updates

1. Apache Doris Data Source Support

Because Apache Doris is frequently used in the community, this release officially includes it in platform support and covers multiple modules:

• Data Connections: supports creating Apache Doris data sources.
• Data Query: supports SQL query capabilities based on Apache Doris.
• Data Integration tasks:
  • Table input tasks support Apache Doris.
  • Table output tasks support Apache Doris.

2. Added Audit Rules

To improve Data Quality validation capabilities, this release adds the following audit rules:

• Time field sequence logic validation: checks whether unreasonable ordering relationships exist between time fields.
• Field group completeness validation: checks whether specified field combinations are unique across the full table, helping identify duplicate or conflicting data.

3. Added Transformation Components

In the transformation stage of Data Integration tasks, multiple commonly used components were added to further improve data processing efficiency and flexibility:

• Duplicate record removal component.
• Constant transformation component.
• Field selection and field editing components.
• Value mapping component.

🐛 Community Bug Fixes

Thanks to continuous feedback from community users, this release fixes the following issues:

• In the Data Quality module, regular expression logic for field character type validation was inconsistent during monitoring, sampling, and task execution.
  https://gitee.com/qiantongtech/qData/issues/ID7JBF
• The top menu had an abnormal page issue when message reminders were set to "mark all as read".
  https://gitee.com/qiantongtech/qData/issues/IDK90M

v1.1.1 - 2026-01-15

This update mainly includes the following improvements:

• Core optimization: The incremental synchronization mechanism is upgraded to a "dynamic cursor" mode, greatly reducing repeated queries and data transfer costs.
• New source support: Adds support for SQL Server 2008, covering connections, queries, and some integration tasks.
• Process standardization: Unifies the Issue submission process template to improve communication and collaboration efficiency.
• Issue fixes: Fixes known bugs reported by the community.

✨ Major Updates

1. Dynamic Cursor Incremental Synchronization Mechanism

To reduce repeated scanning of historical data when incremental synchronization tasks run repeatedly, this release adjusts the incremental synchronization mechanism from "fixed incremental conditions" to "dynamic cursor advancement".

1.1 Primary Key Increment

• Original logic: Incremental conditions were fixed, such as id > fixed value or a fixed range, so repeated task execution could rescan already synchronized data.
• New logic: After task execution completes, the maximum primary key value synchronized in this run is recorded as the cursor. The next execution automatically uses primary key > previous cursor as the incremental condition.
• Applicable scenarios: Tables whose primary keys increase monotonically and can be used for sorting, such as auto-increment IDs.

1.2 Time Increment

• Original logic: A fixed start time had to be configured, such as create_time >= 2025-11-24. Each execution scanned from the fixed start point to the latest data, causing the time window to expand gradually.
• New logic: After task execution completes, the end time of this synchronization window is recorded as the cursor. The next execution uses the previous end time as the current start time, forming a rolling time window.
• Applicable scenarios: Synchronization scenarios that use time fields as the incremental basis.

1.3 Cursor Information Display

• Cursor information is added to task configuration or task details to view the current incremental progress position and the next execution start point.

2. SQL Server 2008 Data Source Support

In response to community needs, this release is backward compatible with SQL Server 2008. The support scope is as follows:

• Data Connections: supports creating SQL Server 2008 data sources.
• Data Query: supports standard SQL queries for this data source.
• Data Integration tasks: supports table input and table output components.

Note: The above support only covers the listed components or task types. Components not mentioned are not adapted yet.

3. Added Cleansing Rules

The following field cleansing rules are added to unify data formats and improve data processing consistency:

• Convert field values to lowercase: uniformly converts field values to lowercase, suitable for fields such as emails and domain names.
• Remove field spaces: removes leading and trailing spaces and cleans extra internal spaces.
• Unified date format: uniformly converts different date formats to a specified standard format, such as yyyy-MM-dd, and supports configurable templates.

4. Issue Template Upgrade

To improve issue positioning efficiency, we standardized the Issue submission process:

• Structured standardization: unifies ticket fields and requires environment information and reproduction steps.
• Filling guidance: provides detailed filling prompts as placeholders in the template.
• Reduced communication cost: information is more concentrated, making it easier for developers to trace and reproduce issues quickly.

🐛 Community Issue Fixes

Thanks to community partners for their feedback. The following issues have been fixed in this release:

• Error when editing a test user's role @xumingliang2020 https://gitee.com/qiantongtech/qData/issues/IDDCKX
• Collection type not taking effect when creating a new API in Data Services wizard mode @jackwong123 https://gitee.com/qiantongtech/qData/issues/ID6J6F

v1.1.0 - 2025-12-19

This release mainly focuses on deep expansion of Data Governance capabilities and full adaptation of system architecture. For complex data scenarios, we greatly expanded the cleansing and audit rule libraries. At the underlying architecture level, we implemented seamless support for ARM + x86 dual architecture and refactored the build process, significantly improving compatibility and deployment efficiency in domestic innovation environments.

🛠 Major Updates

1️⃣ Rule Engine Enhancement

Data Cleansing Rules Extension

• Adds an expired record cleansing rule, supporting automatic identification and processing of time-sensitive data.
• Adds field value uppercase conversion and decimal place unification rules, improving data standardization processing capabilities.
• Adds overlong field truncation to prevent storage overflow caused by abnormal data.
• Adds a regular expression replacement rule to meet complex unstructured text cleansing needs.

Data Audit Rules Extension

• Adds numeric range validation to ensure the reasonableness of key indicator data.
• Adds field length range validation to strengthen monitoring of abnormal input data.
• Adds enumeration validation, supporting compliance checks for specific dictionary value ranges.

2️⃣ Architecture and Deployment Upgrade

Multi-architecture Compatibility

• Fully supports ARM + x86 dual architecture: perfectly adapts to domestic servers such as Kunpeng and Phytium, as well as Apple Silicon development environments, solving cross-platform compatibility issues.
• Completes Dameng database ARM image adaptation, supporting stable operation in domestic innovation environments.

Delivery and Build Optimization (Important)

• Alibaba Cloud image direct connection: images are now hosted in the Alibaba Cloud image repository, so there is no need to download and transfer GB-level offline installation packages. During deployment, you only need to configure the image address for automatic pulling, eliminating slow transfer and oversized package issues.
• One-click build upgrade: supports Maven one-click packaging of JAR packages + Docker images, with configurable options, greatly simplifying release and delivery processes.

⚙️ Underlying Configuration Changes

1. Environment Dependency Adjustment

When using the newly added "one-click image packaging" feature, make sure the build server or development environment has Docker and Buildx installed in advance.

2. Deployment Method Change

Recommended method: directly configure the Alibaba Cloud image source for pull-based deployment (Docker Pull) to get the fastest deployment experience.

⚠️ Upgrade Tip:

1. This update involves underlying architecture and database driver adaptation. If your server uses the ARM architecture, be sure to pull the latest corresponding image version.
2. You no longer need to download a large number of images from Baidu Netdisk.

v1.0.8 - 2025-12-12

This release mainly synchronizes core logic fixes from the commercial edition and addresses open-source community issue feedback. It focuses on strengthening Data Development workflow stability and optimizing multiple UI/UX interaction details, improving overall usability and operating experience.

🛠 Major Updates

1. Core Fixes and Stability

Data Development and Operations

• Fixes the 404 error when saving Data Integration task configuration and the issue where the page did not redirect correctly after confirmation.
• Fixes abnormal Data Development instance request parameters and ineffective filters for execution engine and processing type.
• Fixes invisible code caused by hovering in the Data Query editor area and export errors for query results.
• Fixes project context reset after refreshing the page with F5. The selected project is now retained.
• Fixes possible category loading exceptions when switching projects.
• Fixes errors when calling Data Services with Schema mode names and log permission control exceptions.
• Fixes log download errors for Data Integration and Data Development instances in Operations Management.

Data Standards and Assets

• Fixes batch delete logic for Logical Models, allowing deletion only when the status is disabled, and standardizes Chinese name replacement logic.
• Fixes the issue where Standard Data Elements could still be deleted while enabled.
• Fixes the boundary issue where overly long Data Asset names caused errors, and changes the default asset status to unpublished.
• Corrects incorrect prompt text in registration forms and project assets.

System Management

• Fixes incorrect initialization of preset roles and missing administrator display after adding a project.
• Fixes incorrect operator information display in the system log list.

2. Feature Enhancements and Experience Optimization

• Home overview: optimizes governance data volume trend chart logic and displays full data curves by default.
• Operation logs: improves detail dialog visual style and changes the operator field from account to nickname.
• Global style: standardizes right alignment for buttons and text in lists.
• Operations tools: adds a graph zoom tool to the Data Integration instance detail page for easier viewing of complex task flows.
• Standard registration: splits standard number and name filters, sorts the list by creation time descending, and upgrades the status field to tag display.
• Asset map: optimizes topic display with collapse and expand support, and adds asset selection logic.
• Input guidance: optimizes search prompt copy in the left category areas for Basic Management and Cleansing Rules.
• Redundancy cleanup: removes meaningless code filters from Basic Management, Cleansing Rules, and Application Management filter areas.

3. New Features

• Category management: adds a category management menu for standard classifications.
• Field filtering: supports filtering valid fields across multiple category trees.

4. Underlying Configuration Changes

• The backend configuration item ds.spark.main_jar has removed the outdated 3.8.8 dependency. Check related deployment configurations.
• Corrects version management in pom.xml to ensure accurate build artifact version identifiers.
• This update involves backend logic fixes and frontend resource changes. After deployment, force-refresh browser cache to load the latest UI styles and interactions.

📌 Version Summary

qData v1.0.8 focuses on stability fixes and experience optimization across Data Development, Data Assets, and System Management, providing a more reliable foundation for subsequent feature evolution.

v1.0.7 - 2025-11-07

qData v1.0.7 comprehensively improves database compatibility and deployment flexibility. It adds SQL Server support, improves MySQL adaptation and one-click deployment capabilities, and optimizes the interface and log functions to make the system more stable and easier to use.

🧩 Additions and Enhancements

• Full SQL Server database support: Data Connections, Data Quality, Data Integration, and API publishing modules have all been adapted, covering core feature scenarios.
• MySQL automatic adaptation: Adds MySQL initialization scripts for automatic database and table creation. The system primary database can freely switch between MySQL and Dameng (DM8).
• Flexible deployment upgrade: The .env file supports flexible definition of database types, and the one-click deployment script automatically identifies the primary database type for easy switching.

🎨 Optimizations and Fixes

• Optimizes standard search cards and data asset card styles, making interface display simpler and clearer.
• Improves log module and page loading performance, making browsing smoother.
• Fixes the standard registration field null value issue and Data Integration task configuration jump exception (404).
• Improves Open-Source Edition deployment documentation, supplementing command descriptions and operation details for smoother deployment.

⚙️ Version Highlights

qData v1.0.7 provides full compatibility with SQL Server, MySQL, and Dameng databases.
Combined with optimized logs and frontend experience, it provides stronger support for stable operation and flexible deployment of the data middle-platform.

v1.0.6 - 2025-09-30 National Day Edition

The code name of this release is "Leap of Reconstruction". We completed architecture refactoring for multiple core modules, fully upgraded frontend engineering, and introduced a standard management system, marking a key step toward making qData more professional, stable, and easy to use.

✨ Core Highlights

🎁 Brand-new Demo Data: What You See Is What You Get, Ready Out of the Box

• Built-in complete real-scenario demo data, covering the full process of data access, governance, development, services, analytics, and visualization.
• New users do not need to prepare data. After logging in, they can immerse themselves in the full data middle-platform chain and quickly understand core concepts and operation logic.
• Major pages add new user guidance prompts to help first-time users get started easily and reduce learning costs.

✨ Added Features

📎 Standard system management (brand-new module)
Builds a unified data standard system and improves data normalization and consistency.

• National standard management
• Industry standard management
• Local standard management
• Group standard management
• Standard search function: quickly finds required standards and supports multi-dimensional filtering and fuzzy search.

Data standardization takes a key step forward, helping enterprises build a high-quality data asset foundation.

🔁 Core Module Refactoring

1. Data Connections optimization: improves connection configuration flexibility and stability, supporting more scenarios.

2. Data Query refactoring: improves query performance, refines permission control, and makes the user experience smoother.

3. Task Management module refactoring

• Unified management of Data Integration and Data Development tasks.
• Task category management is clearer, supporting categorized organization and quick positioning.

4. Comprehensive frontend engineering upgrade

• Refactors the overall file directory structure to improve code maintainability.
• Standardizes URL request paths and improves system extensibility and frontend-backend collaboration efficiency.

🐞 Key Bug Fixes (Partial List)

We focused on fixing 80+ key issues reported by users, covering permissions, forms, interactions, data display, and many other areas.

v1.0.5 - 2025-09-03

This update focuses on integrated rule governance, unstructured data support, and Open-Source Edition experience and deployment optimization, comprehensively improving rule reuse capabilities, data access breadth, and O&M efficiency.

✨ Added Features

• 🧩 Field-level rule binding
  Bind audit and cleansing rules to fields in data metadata types. During task and component configuration, rules can be automatically loaded and edited again, reducing repeated configuration.
• 🗂 Unstructured data ETL
  Supports extraction, parsing, cleansing, and loading of file-based and semi-structured data such as CSV and JSON. It provides field mapping, formatting, and validation capabilities, extending Data Governance capabilities.

🔧 Feature Optimizations

• 🔗 Rule linkage and component refactoring
  Transformation components and quality tasks can automatically inherit field rules, making the logic clearer and assembly more efficient.
• 🏠 Open-Source Edition home UI refactoring
  The interface is refreshed, simpler, more intuitive, and provides more complete information display.
• 🧰 Deployment and Operations optimization
  • Quick deployment scripts are upgraded to support environment self-check, health checks, and offline image import.
  • Log functionality is restored: standard output and file logs are both available, making troubleshooting and monitoring easier.
  • Deployment decoupling: DS and backend services can be deployed separately for flexible composition.

v1.0.4 - 2025-09-01

This release focuses on transformation component refactoring (data cleansing), cleansing rule expansion, and asset management upgrades, further improving data processing flexibility and asset management experience.

🔧 Feature Optimizations

• 🔧 Transformation component refactoring: supports binding multiple cleansing rules, enhancing data processing flexibility and extensibility.
• 🧾 Asset management optimization: refactors Data Assets and Project Assets modules, making list and detail display logic more reasonable.
• 🎨 Interface experience upgrade: comprehensively optimizes the asset management interface, with clearer interactions and more intuitive layout.

✨ Added Features

• 🆕 Cleansing rule expansion: adds 5 commonly used cleansing rules, enriching Data Governance capabilities.
• 📝 Asset quality task module: adds quality task configuration and result display on the asset details page, strengthening asset quality control capabilities.

v1.0.3 - 2025-08-26

This release mainly enhances features around Data Quality and audit management, adding task management and reporting capabilities to improve quality control traceability and closed-loop governance.

✨ Added Features

• 🆕 Data Quality task management: supports unified configuration, scheduling, and management of quality tasks.
• 📊 Data Quality task reports: automatically generates task reports and visually presents Data Quality results.

🔧 Feature Optimizations

• 📋 Audit rule supplement entry: adds 3 audit rules to enrich the rule library.
• 📝 Execution log records: adds task execution logs to support issue tracing and troubleshooting.

v1.0.2 - 2025-08-13

This release mainly optimizes and adjusts the frontend interaction and interface of Data Development-related functions, improving user experience and readability.

✨ Optimization Content

• ⚡ Performance optimization: improves Data Development execution efficiency and stability.
• 🗓 Scheduling optimization: task scheduling strategies are more flexible and support multiple execution plans.
• 🧮 Multi-database support optimization: optimizes execution and scheduling experience for Dameng DM, MySQL, Oracle, and Kingbase.
• 🔧 Execution type optimization: Run Once, scheduled execution, and basic configuration execution processes are smoother.
• 🖼 Interface refactoring: adjusts layout and table styles, reduces redundant information, and improves readability.
• 🎆 Interaction optimization: unifies button styles and operation logic, reducing unnecessary clicks.

💡 Tip: We recommend upgrading to qData v1.0.2 for a smoother Data Development and scheduling experience.

v1.0.1 - 2025-08-06

This release focuses on optimizing the Data Development - Data Integration module and adds multiple data processing components, enhancing the stability and flexibility of ETL processes.

✅ Highlights

• 🔧 Refactored Data Integration module: improves data processing efficiency and stability, supporting more flexible task scheduling and execution management.
• 🔘 Sort record transformation component released: supports sorting data by specified fields, improving processing flexibility and convenience.
• ⚡ Field derivation component released: supports deriving new fields from existing fields to meet complex data processing requirements.

🛠 Feature Enhancements

• 🧩 Support for multiple data source connections and scheduling optimization: expands more data source types and optimizes execution efficiency.
• 🧩 Enhanced data cleansing rules: adds multiple rules and supports more fine-grained configuration.

🐞 Bug Fixes

• 🔧 Fixes ETL task abnormal interruption issue, which could occur in specific cases due to network or resource problems.
• 🔧 Fixes field type conversion exception, ensuring the transformation process is more stable and reliable.

📚 Documentation Updates

• 🖼 SQL script updates

  • Dameng database: dm_v1_0_1.sql
  • MySQL database: mysql_v1_0_1.sql

v1.0.0 - 2025-05-26

• 🎉 Initial version released.
• Includes core functions such as System Management, Data Integration, Data Development, and Data Services.