ClickHouse vs StarRocks vs Presto vs Trino vs Apache Spark™ — Comparing Analytics Engines

The blog post delves into the rapidly evolving analytics landscape, focusing on the architecture and trade-offs of five distributed analytics engines: Apache Spark, PrestoDB, Trino, StarRocks, and ClickHouse. These engines are categorized into General Purpose, Interactive SQL, and Realtime OLAP, each serving distinct use cases, from versatile batch processing to fast ad-hoc querying and high-speed real-time analytics. The analysis covers their architectural designs, scalability, concurrency, storage support, and language capabilities, emphasizing factors such as SIMD support, caching, elastic scaling, concurrency management, and support for various file and table formats. Apache Spark stands out for its broad ecosystem, storage, and language support, while Trino and Presto shine in interactive SQL capabilities. StarRocks and ClickHouse offer high-speed OLAP operations with vectorization. The post underscores the importance of choosing an engine based on technical, business, and strategic needs, promoting a flexible approach to leveraging multiple engines within the Onehouse platform for optimized data management and analytics.

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