DotNetNext/SqlSugar

.Net aot ORM SqlServer ORM Mongodb ORM MySql 瀚高 Postgresql ORM DB2 Hana 高斯 Duckdb C# VB.NET Sqlite ORM Oracle ORM Mysql Orm 虚谷数据库 达梦 ORM 人大金仓 ORM 神通ORM...

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Summary Information

Updated 14 minutes ago
Added to GitGenius on September 11th, 2026
Created on July 13th, 2015
Open Issues & Pull Requests: 14 (+0)
GitHub issues: Enabled
Number of forks: 1,389
Total Stargazers: 5,831 (+0)
Total Subscribers: 259 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 4.4 hours
Mean response time: 11.7 days
90th percentile: 2.8 days
Tracked items: 103

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 13% of issues opened in the past year have been closed. Three people close 73% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 13
New in 7 days: 2
Closed in 7 days: 0
Avg open age: 192 days
Stale 30+ days: 10
Stale 90+ days: 6

Recent activity

Opened in 7 days: 2
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Most active issues this week

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Detailed Description

SqlSugar is a .NET object-relational mapping framework that supports multiple database systems and .NET versions from the framework through .NET 10.

The tool addresses the need for a lightweight ORM that minimizes boilerplate code while maintaining performance across diverse database platforms. It achieves this through a zero-SQL approach where table creation, indexing, and CRUD operations require no manual SQL writing. The framework supports both entity-based and dynamic operations, allowing developers to work with or without predefined entity classes. It includes specialized handling for large-scale data operations, multi-tenancy scenarios with database and table sharding, and cross-database queries within a single application.

SqlSugar suits teams building applications on .NET that need to work with multiple database backends without rewriting data access logic. It is particularly valuable for projects requiring multi-tenancy support, high-volume data operations, or compatibility with both mainstream databases like MySQL, SQL Server, and PostgreSQL alongside specialized systems like ClickHouse, MongoDB, and various Chinese domestic databases. The framework's support for dynamic operations and JSON-to-SQL conversion makes it applicable to low-code scenarios and applications with flexible schema requirements.

The maintainers typically respond to new issues and pull requests within a day.