Anyline

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The core of AnyLine is a runtime-oriented dynamic metadata mapping system that is compatible with over 100 relational and non-relational databases.
It is often used as the underlying support for dynamic structure scenarios, appearing as an SQL parsing engine or adapter.
【Document】 【Quick Start】 【Applicable Scenarios】 【Architecture Diagram】

Vision

Relying on a dialect conversion engine and metadata mapping library synthesized by built-in rules and external plugins,
we aim to establish a universal standard across databases on this foundation, enabling unified operations on heterogeneous databases.

Core Concept

AnyLine MDM focuses on ‌runtime metadata dynamic mapping‌, primarily used for operating database structures, reading/writing metadata, and providing underlying support for dynamic scenarios. It often acts as an ‌SQL synthesis engine‌ or ‌adapter‌ in contexts such as:

• Data middle platforms
• Visualized data sources
• Low-code platforms
• SaaS applications
• Custom forms
• Heterogeneous database migration and synchronization
• IoT/vehicle network data processing
• Dynamic forms and query conditions
• Web crawler data parsing

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Core Features

1. ‌Dynamic Data Source Management‌

• Supports runtime dynamic registration, switching, and deregistration of various data sources.
• Provides ‌7 data source registration methods‌ and ‌3 switching mechanisms‌.

2. ‌Database Structure and Metadata Management‌

• Supports dynamic management of database structures (e.g., automatic table creation, field extension).
• Standardizes metadata collection (data types, comments, constraint rules) for unified governance of data structures and metadata.
• Enables ‌table structure difference comparison‌, ‌heterogeneous database structure replication‌, and ‌data synchronization‌.

3. ‌Dynamic DDL‌

• Generates cross-database dynamic DDL by comparing metadata, analyzing table structure differences.
• Supports field type mapping, constraint conversion, indexing, etc., commonly used in database migration and version synchronization.

4. ‌Dynamic Query Conditions‌

• Provides metadata-driven dynamic query solutions for flexible data filtering, sorting, and pagination.
• Supports multi-layer complex condition combinations and cross-database compatibility.
• Automatically generates query conditions in formats like JSON, String, or ConfigStore, ideal for low-code platforms to avoid cumbersome judgments, traversals, and format conversions while maintaining high performance and maintainability.

5. ‌Database Compatibility and Adaptation‌

• Unifies database dialects for seamless metadata object compatibility across databases (relational, key-value, time-series, graph, document, columnar, vector, search, spatial, RDF, Event Store, Multivalue, Object).
• Specifically supports domestic databases.

6. ‌In-Memory Computation for Dynamic Data Structures (DataSet<DataRow>)‌

• Based on a dynamic expression engine and SQL-like filtering, with built-in mathematical formulas, enables one-click aggregation, filtering, pivoting, and other operations on result sets, avoiding cumbersome ORM traversal.

7. ‌Multi-Data Source Transaction Management‌

• Supports arbitrary data source switching while maintaining multiple transaction states and cross-thread transactions.

8. ‌Permission Management‌

• Manages roles, users, and permissions.

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Why Use AnyLine Instead of Traditional ORM?

1. ‌Target Scenarios‌

• ‌AnyLine‌: Designed for highly dynamic runtime scenarios, natively supporting runtime uncertainties.

  • Handles dynamic data source access requests with heterogeneous structures and protocols.
  • Adapts to real-time changes in metadata (e.g., table structures, field definitions).
  • Provides dynamic model reconstruction and query adaptation through metadata management and adaptive mapping.

• ‌Traditional ORM‌: Suited for static or relatively stable business scenarios.

  • Relies on predefined database structures and entity relationships during development.
  • Ensures system stability with upfront modeling and design.

2. ‌Product Positioning‌

• ‌AnyLine‌: Targets middleware development platforms for building low-code platforms, dynamic query engines, etc.

  • Empowers end-users to create customized business applications via visual configuration (e.g., dynamic reports, data analysis views).

• ‌Traditional ORM‌: Used for developing end-user business systems (e.g., ERP, CRM, OA).

  • Maps database tables to object models for object-oriented database operations.

3. ‌Operation Targets‌

• ‌AnyLine‌: Metadata-driven, abstracting data structures and business logic.

  • Allows dynamic configuration of data models and business rules during early project stages.
  • Adapts to changing business requirements without a complete object model.

• ‌Traditional ORM‌: Operates on entity classes directly mapped to database tables.

  • Maps tables to programming language classes, with fields and relationships reflected as class properties and associations.

4. ‌Target Users‌

• ‌AnyLine‌: For system architects and framework developers building highly flexible, extensible systems.

  • Provides runtime data structure and business rule definition capabilities.
  • Addresses system reconfiguration challenges due to requirement changes.

• ‌Traditional ORM‌: For application developers building relational database-backed systems.

  • Simplifies database access and improves development efficiency.

5. ‌User Requirements‌

• ‌AnyLine‌: Requires deeper technical expertise, especially in metadata-driven development and dynamic system design.

  • Users must understand dynamic data model design and translate business requirements into configurable metadata rules.

• ‌Traditional ORM‌: Easier to learn and use, lowering the database operation threshold for developers.

6. ‌Design Philosophy and Implementation‌

| Aspect | AnyLine | Traditional ORM (e.g., Hibernate) | |-----------------------|-------------------------------------------------------------------------|-----------------------------------------------------------| | ‌Dynamic vs Static‌ | Runtime metadata-driven, supports dynamic data source registration. | Relies on static entity class and database table pre-mapping. | | ‌Metadata vs Object‌| Operates on database structures (tables, views, columns) and metadata. | Operates indirectly via object models (classes/properties). | | ‌Multi-Database‌ | Adapts dynamically via metadata engine and SQL dialect conversion. | Requires hardcoded entity classes and dialect configuration. |

‌DataSet/DataRow vs Traditional ORM Entity Class‌

| Dimension | AnyLine (DataSet/DataRow) | Traditional ORM (Entity Class) | |-------------------------|------------------------------------------------------------|---------------------------------------------------------| | ‌Data Representation‌ | Dynamic structure (DataRow = row, DataSet<DataRow> = table). | Static strongly-typed classes (e.g., User.java). | | ‌Flexibility‌ | Adapts to table structure changes dynamically. | Requires code changes for table structure modifications.| | ‌Query Result Handling‌| Directly operates on dynamic result sets. | Requires DTOs or projection interfaces. | | ‌Low-Code Support‌ | Suitable for dynamic forms and ad-hoc queries. | Requires predefined entity classes. | | ‌Performance Overhead‌| Lightweight, no reflection/proxy generation. | May incur overhead due to reflection/bytecode enhancement. | | ‌Complex Mapping‌ | Manual handling by default (e.g., multi-table JOIN results).| Automatically manages associations (e.g., @OneToMany).| | ‌Use Cases‌ | Dynamic business scenarios, heterogeneous databases. | Fixed business models (e.g., ERP, CRM). |

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How AnyLine Works

Key Components

1. ‌Parsing Layer‌: Automatically converts standard SQL syntax into database-specific dialects.
2. ‌Metadata Abstraction Layer‌: Builds a unified data view to shield structural