Citus vs Clickhouse: What are the differences?

Introduction:

Citus and Clickhouse are two popular database management systems with distinctive features and use cases. In this comparison, we will highlight six key differences between Citus and Clickhouse.

1. Scalability: Citus is a distributed database that scales horizontally by distributing data across multiple nodes, offering linear scalability. It uses sharding to divide the data into smaller chunks and replicates them across different servers. On the other hand, Clickhouse is designed for high-performance analytics and supports massively parallel processing. It horizontally scales by adding more servers and using replication for fault tolerance.

2. Data Model: Citus is an extension of PostgreSQL, providing SQL querying capabilities and supporting JSON and other PostgreSQL data types. It allows for transactional consistency and supports relational data models with joins and foreign keys. In contrast, Clickhouse is a columnar database optimized for analytical workloads, focusing on read-heavy operations. It uses a denormalized data model and does not support joins or transactions.

3. Data Compression: Citus supports compression techniques to reduce storage costs and improve query performance. It uses PostgreSQL's built-in compression mechanisms for data compression and decompression. Clickhouse also provides data compression techniques, but it employs column-wise compression, which greatly reduces storage requirements and improves query execution speed.

4. Query Execution: Citus executes queries by parallelizing them across distributed nodes, processing smaller chunks of data in parallel. It utilizes distributed query planning and optimization techniques to achieve efficient query execution. Clickhouse, being an analytics-focused database, accelerates query execution through vectorized query processing. It performs operations on data in batches, which significantly improves performance compared to row-based processing.

5. Data Replication: Citus offers replication capabilities to ensure data availability and fault tolerance. It uses PostgreSQL's streaming replication to replicate data across different nodes. This enables automatic failover and provides high availability. In contrast, Clickhouse replicates data using the Raft consensus protocol, which ensures strong consistency for distributed deployments. It supports synchronous and asynchronous replication depending on the desired level of data consistency.

6. Data Partitioning: Citus partitions the data based on a sharding key to distribute it across different nodes. It manages the data placement and routing of queries to the appropriate shards. This allows for efficient data distribution and parallel query execution. Clickhouse, on the other hand, partitions data based on its internal data structure, known as a "part". Each part represents a subset of data, enabling efficient storage and query execution.

In Summary, Citus offers scalable distributed database capabilities with transactional consistency, while Clickhouse excels at high-performance analytics with columnar storage, vectorized query processing, and efficient data replication.