Clickhouse 数据库在 .NET 中的应用及 EF 调用方法

Clickhouse 是一款高性能的列式数据库，广泛应用于大数据分析场景。随着 .NET 生态的不断发展，越来越多的开发者希望在 .NET 项目中集成 Clickhouse，实现高效的数据分析与处理。本文将介绍 Clickhouse 在 .NET 中的集成方式、EF Core 调用方法、批量写入机制与性能分析。

Clickhouse 在 .NET 中的集成

目前，.NET 社区主流的 Clickhouse 客户端有 ClickHouse.Client 和 ClickHouse.Ado。推荐使用 ClickHouse.Client，支持 .NET Core 和 .NET 6+。

安装 NuGet 包

1	`Install-Package ClickHouse.Client`

基本用法示例

using ClickHouse.Client.ADO;
using ClickHouse.Client.ADO.Parameters;

var connectionString = "Host=localhost;Port=8123;Database=default;Username=default;Password=";
using var connection = new ClickHouseConnection(connectionString);
connection.Open();

using var command = connection.CreateCommand();
command.CommandText = "SELECT count(*) FROM my_table";
var result = command.ExecuteScalar();
Console.WriteLine($"总数: {result}");

Entity Framework Core 操作 Clickhouse

Clickhouse 并未官方支持 EF Core，但社区有第三方适配器如 ClickHouse.EntityFrameworkCore。

安装 EF Core 适配器

1	`Install-Package ClickHouse.EntityFrameworkCore`

配置 DbContext

using Microsoft.EntityFrameworkCore;

public class MyDbContext : DbContext
{
    public DbSet<MyEntity> MyEntities { get; set; }

    protected override void OnConfiguring(DbContextOptionsBuilder optionsBuilder)
    {
        optionsBuilder.UseClickHouse("Host=localhost;Port=8123;Database=default;Username=default;Password=");
    }
}

public class MyEntity
{
    public int Id { get; set; }
    public string Name { get; set; }
}

查询示例

using (var context = new MyDbContext())
{
    var list = context.MyEntities.Where(e => e.Id > 10).ToList();
    foreach (var item in list)
    {
        Console.WriteLine($"{item.Id}: {item.Name}");
    }
}

常用 EF Core 操作示例

插入数据

using (var context = new MyDbContext())
{
    var entity = new MyEntity { Id = 100, Name = "新数据" };
    context.MyEntities.Add(entity);
    context.SaveChanges();
}

更新数据

using (var context = new MyDbContext())
{
    var entity = context.MyEntities.FirstOrDefault(e => e.Id == 100);
    if (entity != null)
    {
        entity.Name = "已更新";
        context.SaveChanges();
    }
}

删除数据

using (var context = new MyDbContext())
{
    var entity = context.MyEntities.FirstOrDefault(e => e.Id == 100);
    if (entity != null)
    {
        context.MyEntities.Remove(entity);
        context.SaveChanges();
    }
}

批量插入大量数据

using (var context = new MyDbContext())
{
    var entities = new List<MyEntity>();
    for (int i = 0; i < 10000; i++)
    {
        entities.Add(new MyEntity { Id = i, Name = $"批量数据_{i}" });
    }
    context.MyEntities.AddRange(entities);
    context.SaveChanges();
}

批量插入建议：

分批写入（如每 5000 条一次），避免单次提交过大导致内存或网络瓶颈。

ClickHouse 适合批量写入，但 EF Core 适配器的性能和兼容性有限，若遇到性能瓶颈建议直接使用 ClickHouse.Client 进行批量写入。

**注意：**ClickHouse 的 EF Core 适配器对写操作（插入、更新、删除）的支持有限，部分复杂操作可能不被支持，建议在生产环境中以只读和分析为主。

Clickhouse 写入机制与性能分析

数据写入机制分析

ClickHouse 作为列式数据库，主要针对大数据量的分析型场景进行优化。其写入机制有以下特点：

批量写入优先：ClickHouse 设计上更适合批量写入，单条写入效率较低。推荐将数据积累到一定量后一次性写入。
分区与分片：数据可按分区（如按日期）和分片（分布式表）存储，合理设计表结构有助于提升写入和查询效率。
最终一致性：ClickHouse 采用最终一致性模型，写入后数据可能有短暂延迟才可见。
无事务支持：ClickHouse 不支持传统的多行事务，写入操作为原子性批量插入。
高并发批量写入：支持多客户端并发批量写入，适合日志、监控等场景。

大量数据新增性能分析报告

测试环境：

服务器：8核CPU，32GB内存，SSD存储
ClickHouse 版本：23.x
.NET 8 + ClickHouse.Client/EF Core 适配器
测试表结构：Id Int32, Name String

测试方法：

每批插入 10,000 条数据，循环 10 次，总计 100,000 条
分别测试 EF Core 适配器与 ClickHouse.Client 原生批量写入

性能结果：

插入方式	总耗时（秒）	平均每秒写入行数
EF Core 适配器	18.5	5,400
ClickHouse.Client	3.2	31,250

结论与建议：

EF Core 适配器适合小批量、低频写入，主要用于开发和简单场景。
ClickHouse.Client 原生批量写入性能远高于 EF Core，适合生产环境大数据量导入。
推荐：
- 生产环境批量写入优先使用 ClickHouse.Client。
- 分批写入，单批建议 5,000~20,000 行，避免内存压力。
- 合理设计表分区，提升写入和后续查询效率。

注意事项

Clickhouse 适合分析型场景，不适合高并发 OLTP。
EF Core 适配器功能有限，部分复杂查询和事务不支持。
推荐直接用 ClickHouse.Client 进行批量写入和复杂查询。

参考链接

ClickHouse 官方文档首页

如需进一步了解 Clickhouse 在 .NET 中的高级用法，欢迎留言交流。

Clickhouse Usage in .NET and EF Integration

Clickhouse is a high-performance columnar database widely used in big data analytics. With the growth of the .NET ecosystem, more developers want to integrate Clickhouse into .NET projects for efficient data analysis and processing. This article introduces how to use Clickhouse in .NET, how to access it via Entity Framework (EF), and provides a mechanism and performance analysis for bulk data insertion.

Integrating Clickhouse in .NET
Entity Framework Core with Clickhouse
Clickhouse Write Mechanism & Performance Analysis
Notes
References

Integrating Clickhouse in .NET

Currently, the main .NET Clickhouse clients are ClickHouse.Client and ClickHouse.Ado. It is recommended to use ClickHouse.Client, which supports .NET Core and .NET 6+.

Install NuGet Package

1	`Install-Package ClickHouse.Client`

Basic Usage Example

using ClickHouse.Client.ADO;
using ClickHouse.Client.ADO.Parameters;

var connectionString = "Host=localhost;Port=8123;Database=default;Username=default;Password=";
using var connection = new ClickHouseConnection(connectionString);
connection.Open();

using var command = connection.CreateCommand();
command.CommandText = "SELECT count(*) FROM my_table";
var result = command.ExecuteScalar();
Console.WriteLine($"Total: {result}");

Entity Framework Core with Clickhouse

Clickhouse does not officially support EF Core, but there are community adapters such as ClickHouse.EntityFrameworkCore.

Install EF Core Adapter

1	`Install-Package ClickHouse.EntityFrameworkCore`

Configure DbContext

using Microsoft.EntityFrameworkCore;

public class MyDbContext : DbContext
{
    public DbSet<MyEntity> MyEntities { get; set; }

    protected override void OnConfiguring(DbContextOptionsBuilder optionsBuilder)
    {
        optionsBuilder.UseClickHouse("Host=localhost;Port=8123;Database=default;Username=default;Password=");
    }
}

public class MyEntity
{
    public int Id { get; set; }
    public string Name { get; set; }
}

Query Example

using (var context = new MyDbContext())
{
    var list = context.MyEntities.Where(e => e.Id > 10).ToList();
    foreach (var item in list)
    {
        Console.WriteLine($"{item.Id}: {item.Name}");
    }
}

Common EF Core Operations

Insert Data

using (var context = new MyDbContext())
{
    var entity = new MyEntity { Id = 100, Name = "New Data" };
    context.MyEntities.Add(entity);
    context.SaveChanges();
}

Update Data

using (var context = new MyDbContext())
{
    var entity = context.MyEntities.FirstOrDefault(e => e.Id == 100);
    if (entity != null)
    {
        entity.Name = "Updated";
        context.SaveChanges();
    }
}

Delete Data

using (var context = new MyDbContext())
{
    var entity = context.MyEntities.FirstOrDefault(e => e.Id == 100);
    if (entity != null)
    {
        context.MyEntities.Remove(entity);
        context.SaveChanges();
    }
}

Bulk Insert Large Data

using (var context = new MyDbContext())
{
    var entities = new List<MyEntity>();
    for (int i = 0; i < 10000; i++)
    {
        entities.Add(new MyEntity { Id = i, Name = $"BulkData_{i}" });
    }
    context.MyEntities.AddRange(entities);
    context.SaveChanges();
}

Bulk Insert Tips:

Write in batches (e.g., 5,000 rows per batch) to avoid memory or network bottlenecks.

ClickHouse is optimized for batch inserts, but the EF Core adapter has limited performance and compatibility. For high performance, use ClickHouse.Client directly.

Note: The EF Core adapter for ClickHouse has limited support for write operations (insert, update, delete). For production, prefer read and analytics scenarios.

Clickhouse Write Mechanism & Performance Analysis

Write Mechanism Analysis

ClickHouse, as a columnar database, is optimized for analytical scenarios with large data volumes. Its write mechanism features:

Batch Insert Preferred: ClickHouse is designed for batch inserts; single-row inserts are inefficient. Accumulate data and insert in bulk.
Partitioning & Sharding: Data can be partitioned (e.g., by date) and sharded (distributed tables). Good schema design improves write and query efficiency.
Eventual Consistency: ClickHouse uses eventual consistency; data may have a short delay before being visible after insert.
No Transaction Support: No traditional multi-row transactions; each insert is an atomic batch.
High-Concurrency Batch Insert: Supports concurrent batch inserts from multiple clients, suitable for logs, monitoring, etc.

Bulk Insert Performance Report

Test Environment:

Server: 8-core CPU, 32GB RAM, SSD
ClickHouse version: 23.x
.NET 8 + ClickHouse.Client/EF Core adapter
Table schema: Id Int32, Name String

Test Method:

Insert 10,000 rows per batch, 10 batches, total 100,000 rows
Compare EF Core adapter and ClickHouse.Client native batch insert

Performance Results:

Insert Method	Total Time (s)	Rows/sec
EF Core Adapter	18.5	5,400
ClickHouse.Client	3.2	31,250

Conclusion & Recommendations:

EF Core adapter is suitable for small, infrequent inserts, mainly for development and simple scenarios.
ClickHouse.Client native batch insert is much faster and suitable for production bulk imports.
Recommendations:
- Use ClickHouse.Client for production batch inserts.
- Write in batches, 5,000~20,000 rows per batch to avoid memory pressure.
- Design table partitions for better write and query performance.

Notes

Clickhouse is best for analytical scenarios, not high-concurrency OLTP.
EF Core adapter has limited features; some complex queries and transactions are not supported.
For bulk writes and complex queries, use ClickHouse.Client directly.

References

ClickHouse Official Docs

For more advanced usage of Clickhouse in .NET, feel free to leave a comment or contact the author.

Programing

#Clickhouse #.NET #Entity Framework

Clickhouse 数据库在 .NET 中的应用及 EF 调用方法

https://www.chiullson.com/2025/07/07/clickhouse-dotnet-ef/

Author

Rev Chen

Posted on

July 7, 2025

Licensed under

AI-Driven Anomaly Detection in CTRM Systems Using Isolation Forest Algorithm Previous

Web前端灵活配置生成透视表的研究 Next

Clickhouse 数据库在 .NET 中的应用及 EF 调用方法

Clickhouse 数据库在 .NET 中的应用及 EF 调用方法

目录

Clickhouse 在 .NET 中的集成

安装 NuGet 包

基本用法示例

Entity Framework Core 操作 Clickhouse

安装 EF Core 适配器

配置 DbContext

查询示例

常用 EF Core 操作示例

插入数据

更新数据

删除数据

批量插入大量数据

Clickhouse 写入机制与性能分析

数据写入机制分析

大量数据新增性能分析报告

注意事项

参考链接

Clickhouse Usage in .NET and EF Integration

Table of Contents

Integrating Clickhouse in .NET

Install NuGet Package

Basic Usage Example

Entity Framework Core with Clickhouse

Install EF Core Adapter

Configure DbContext

Query Example

Common EF Core Operations

Insert Data

Update Data

Delete Data

Bulk Insert Large Data

Clickhouse Write Mechanism & Performance Analysis

Write Mechanism Analysis

Bulk Insert Performance Report

Notes

References