Clickhouse vs MongoDB: What are the differences?


In this article, we will discuss the key differences between ClickHouse and MongoDB, two popular database management systems. Both ClickHouse and MongoDB have their own unique features and characteristics that make them suitable for different use cases.

Let's explore the differences between these two databases.

  1. Data Model: ClickHouse is a columnar database that stores data in columns rather than rows. It is optimized for analytical queries and is well-suited for handling large volumes of data. On the other hand, MongoDB is a document-oriented database that stores data in flexible JSON-like documents. It is designed for high availability and scalability, making it suitable for a wide range of applications.

  2. Query Language: ClickHouse uses its own query language called ClickHouse SQL, which is based on SQL but optimized for analytical queries. It supports a wide range of SQL functions and aggregations. MongoDB, on the other hand, uses a query language called MongoDB Query Language (MQL), which is specifically designed for working with JSON-like documents. It supports flexible queries and powerful aggregation pipelines.

  3. Data Replication: ClickHouse supports synchronous and asynchronous data replication mechanisms, allowing data to be replicated across multiple servers for high availability and fault tolerance. It also supports sharding for distributing data across multiple servers. MongoDB also supports replication and sharding for scalability and high availability. It uses a replica set architecture for replication and a sharded cluster architecture for sharding.

  4. Indexing: ClickHouse uses a specialized indexing mechanism called a merge tree, which is optimized for efficient data compression and fast analytical queries. It also supports secondary indices for filtering and indexing specific columns. MongoDB, on the other hand, supports various types of indexes, including single field, compound, multi-key, geospatial, and text indexes. These indexes improve query performance and enable efficient data retrieval.

  5. Durability and Atomicity: ClickHouse is optimized for fast data ingestion and analytical queries but does not provide full ACID (Atomicity, Consistency, Isolation, Durability) compliance. It does not support transactions or rollback mechanisms. MongoDB, on the other hand, provides ACID compliance for individual operations within a single document. It supports transactions, which allow multiple operations to be executed atomically and provide data consistency and durability.

  6. Scalability: ClickHouse is designed to scale horizontally by adding more servers to a cluster. It can handle large-scale distributed analytics workloads and easily scale to petabytes of data. MongoDB also supports horizontal scalability through sharding, allowing data to be distributed across multiple servers. It can handle high write and read loads and scale to handle large datasets.

In summary, ClickHouse is a columnar database optimized for analytical queries, while MongoDB is a document-oriented database suited for flexible data storage and high availability. ClickHouse excels in handling large-scale analytics workloads, while MongoDB provides rich querying capabilities and ACID compliance.

数据模型:ClickHouse 是一种列式数据库,它将数据存储在列而不是行中。它针对分析查询进行了优化,非常适合处理大量数据。另一方面,MongoDB 是一种面向文档的数据库,它将数据存储在灵活的类似 JSON 的文档中。它专为高可用性和可扩展性而设计,适用于各种应用程序。

查询语言:ClickHouse 使用自己的查询语言 ClickHouse SQL,它基于 SQL 但针对分析查询进行了优化。它支持各种 SQL 函数和聚合。另一方面,MongoDB 使用一种称为 MongoDB 查询语言(MQL)的查询语言,专门用于处理类似 JSON 的文档。它支持灵活的查询和强大的聚合管道。

数据复制:ClickHouse 支持同步和异步数据复制机制,允许数据在多个服务器之间复制,以实现高可用性和容错性。它还支持分片,用于在多个服务器之间分发数据。MongoDB 也支持复制和分片,以实现可扩展性和高可用性。它使用复制集架构进行复制,使用分片集群架构进行分片。

索引:ClickHouse 使用一种称为合并树的专门索引机制,该机制针对高效数据压缩和快速分析查询进行了优化。它还支持用于过滤和索引特定列的二级索引。另一方面,MongoDB 支持各种类型的索引,包括单字段、复合、多键、地理空间和文本索引。这些索引提高了查询性能,并实现了有效的数据检索。

持久性和原子性:ClickHouse 针对快速数据摄入和分析查询进行了优化,但不提供完整的 ACID(原子性、一致性、隔离性、持久性)兼容性。它不支持事务或回滚机制。另一方面,MongoDB 为单个文档内的操作提供 ACID 兼容性。它支持事务,允许原子地执行多个操作,并提供数据一致性和持久性。

可扩展性:ClickHouse 的设计是通过向集群中添加更多服务器来实现水平扩展。它可以处理大规模的分布式分析工作负载,并轻松扩展到 PB 级数据量。

MongoDB 也支持通过分片实现水平扩展,允许数据分布在多个服务器上。它可以处理高写入和读取负载,并扩展以处理大型数据集。 总之,ClickHouse 是一种针对分析查询进行优化的列式数据库,而 MongoDB 则是一种适用于灵活数据存储和高可用性的面向文档的数据库。

ClickHouse 擅长处理大规模分析工作负载,而 MongoDB 提供丰富的查询功能和 ACID 合规性。