Apache Kudu vs Clickhouse: What are the differences?

Apache Kudu vs ClickHouse

1. Data Storage: Apache Kudu stores data both in-memory and on disk, whereas ClickHouse primarily stores data on disk in a column-oriented format.

2. Consistency Model: Apache Kudu provides strong consistency with updates and deletes, while ClickHouse focuses on providing eventual consistency for high ingestion rates and query performance.

3. Secondary Indexes: Apache Kudu supports secondary indexes for efficient data retrieval, whereas ClickHouse relies on efficient columnar storage and indexing for query performance.

4. Query Language: ClickHouse primarily uses SQL for querying data, while Apache Kudu allows querying data using languages like SQL, Java, and Python.

5. Scaling: Apache Kudu scales well for real-time analytics and can handle high update rates, while ClickHouse is designed for high-speed analytical queries on large datasets.

6. Use Cases: Apache Kudu is suitable for operational analytics use cases requiring real-time processing, whereas ClickHouse is ideal for OLAP workloads and ad-hoc querying on big data.

In Summary, Apache Kudu and ClickHouse differ in data storage, consistency model, secondary indexes, query language, scaling, and use cases they are best suited for.