The difference between trino and dremio

Apache Trino (formerly known as PrestoSQL) and Dremio are both distributed query engines, but they are designed with different architectures and use cases in mind. Here’s a comparison of the two:

Apache Trino

  1. Query Engine: Trino is a distributed SQL query engine designed for interactive analytic queries against various data sources of all sizes, from gigabytes to petabytes. It’s particularly optimized for OLAP (Online Analytical Processing) queries.
  2. Data Federation: Trino allows querying data where it lives, without the need to move or copy the data. It can query multiple sources simultaneously and supports a wide variety of data sources like HDFS, S3, relational databases, NoSQL databases, and more.
  3. Performance: Trino is designed for fast query execution and is capable of providing results in seconds. It achieves high performance through in-memory processing and distributed query execution.
  4. Use Cases: Trino is primarily used for interactive analytics, where users execute complex queries and expect quick results. It’s suitable for data analysts and scientists who need to perform ad-hoc analysis across different data sources.
  5. Statelessness: Trino’s architecture is stateless, which means it doesn’t store any data itself. It processes queries and retrieves data directly from the source.


  1. Data-as-a-Service Platform: Dremio is not just a query engine; it’s a data-as-a-service platform that provides tools for data exploration, curation, and acceleration. It offers a more integrated solution compared to Trino’s specialized query engine.
  2. Data Reflections: One of Dremio’s key features is its use of data reflections, which are optimized representations of data that can significantly speed up query performance. These reflections allow Dremio to provide faster responses to queries by avoiding full scans of the underlying data.
  3. Data Catalog: Dremio includes a data catalog that helps users discover and curate data. It provides a unified view of all data sources, making it easier for users to find and access the data they need.
  4. Data Lineage: It offers data lineage features, providing visibility into how data is transformed and used across the platform, which is beneficial for governance and compliance.
  5. Use Cases: Dremio is suited for organizations looking for a comprehensive data platform that can handle data exploration, curation, and query acceleration. It’s beneficial for scenarios where performance optimization and data management are critical.


  • Trino is a high-performance, distributed SQL query engine designed for fast, ad-hoc analytics across various data sources. It’s focused on query execution and is best suited for environments where the primary requirement is to run interactive, complex queries over large datasets.
  • Dremio offers a broader set of features beyond just query execution, including data curation, cataloging, and acceleration. It’s designed as a data-as-a-service platform that can help organizations manage and optimize their data for various analytics and BI use cases.

Choosing between Trino and Dremio depends on the specific needs of the organization. If the primary need is fast, ad-hoc query execution across diverse data sources, Trino might be the better choice. If there’s a requirement for a comprehensive data platform with features like data curation, cataloging, and acceleration, Dremio could be more suitable.