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Apache Kudu vs Clickhouse: What are the differences?
Apache Kudu vs ClickHouse
Data Storage: Apache Kudu stores data both in-memory and on disk, whereas ClickHouse primarily stores data on disk in a column-oriented format.
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.
Secondary Indexes: Apache Kudu supports secondary indexes for efficient data retrieval, whereas ClickHouse relies on efficient columnar storage and indexing for query performance.
Query Language: ClickHouse primarily uses SQL for querying data, while Apache Kudu allows querying data using languages like SQL, Java, and Python.
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.
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.
Pros of Apache Kudu
- Realtime Analytics10
Pros of Clickhouse
- Fast, very very fast21
- Good compression ratio11
- Horizontally scalable7
- Utilizes all CPU resources6
- RESTful5
- Open-source5
- Great CLI5
- Great number of SQL functions4
- Buggy4
- Server crashes its normal :(3
- Highly available3
- Flexible connection options3
- Has no transactions3
- ODBC2
- Flexible compression options2
- In IDEA data import via HTTP interface not working1
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Cons of Apache Kudu
- Restart time1
Cons of Clickhouse
- Slow insert operations5
