Clickhouse vs Tarantool: What are the differences?

Introduction

Clickhouse and Tarantool are both open-source databases known for their high performance and scalability. However, they have key differences in terms of their architecture and functionality. Below are the key distinctions between Clickhouse and Tarantool.

1. Data Model: Clickhouse is a column-oriented database, which means it stores data in columns rather than rows, making it highly efficient for analytical queries that involve aggregating data over large datasets. On the other hand, Tarantool is a NoSQL, in-memory, key-value store with support for JSON and SQL interfaces, making it more versatile for different types of data storage and retrieval needs.

2. Query Language: Clickhouse primarily uses SQL (Structured Query Language) for querying data, making it familiar and easy to use for users familiar with SQL databases. Tarantool, on the other hand, utilizes a Lua-based query language, which provides more flexibility and capabilities for developers to customize their data operations and business logic.

3. Storage Engine: Clickhouse relies on a custom storage engine optimized for high-performance analytical workloads, utilizing a combination of memory and disk storage for efficient data processing. Tarantool, on the other hand, is an in-memory database that stores data entirely in RAM, providing ultra-fast data access and low latency for real-time applications.

4. Consistency Model: Clickhouse follows a strong consistency model, ensuring that all reads and writes to the database are consistently and immediately available to all nodes in the cluster. Tarantool, on the other hand, offers eventual consistency by default, where data updates are propagated asynchronously across nodes, potentially leading to temporary inconsistencies in data.

5. Replication and Sharding: Clickhouse supports replication and sharding for horizontal scaling, allowing users to distribute data across multiple nodes for improved performance and fault tolerance. Tarantool also offers replication and sharding capabilities, but it is more focused on providing real-time replication and synchronization features for high availability and data consistency.

6. Use Cases: Clickhouse is ideal for analytical workloads that require fast query performance over large datasets, making it suitable for data warehousing, business intelligence, and analytics applications. Tarantool, on the other hand, is well-suited for real-time applications that demand ultra-low latency and high throughput, such as caching, messaging, and online transaction processing (OLTP) systems.

In Summary, Clickhouse and Tarantool differ in their data models, query languages, storage engines, consistency models, replication and sharding capabilities, and use cases, catering to distinct requirements for analytical and real-time data processing needs.