10億ドキュメント JSON チャレンジ: ClickHouse vs. MongoDB, Elasticsearch, など

I can provide a neutral, objective, and interesting summary of the text in one paragraph. The One Billion Documents JSON Challenge compares the performance of five data storage systems - ClickHouse, MongoDB, Elasticsearch, DuckDB, and PostgreSQL - when handling massive amounts of JSON data. The challenge uses a dataset with 10 billion rows, which is divided into eight subsets to test each system's efficiency. The results show that ClickHouse outperforms the other systems in both storage size and query performance. Specifically, it reduces storage size by up to 99% compared to Elasticsearch, which requires over 360 GB of disk space. Additionally, ClickHouse executes queries faster than the other systems, with a cold run time of just under 1 second for each query. The study highlights the benefits of using a native JSON data type in ClickHouse, which allows for efficient storage and processing of large amounts of JSON data.