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Trino: Scalable, Distributed, and Open Source SQL Engine!

Trino: SQL at any scale, on any storage, in any environment!

Josue Luzardo Gebrim
8 min readMay 30, 2022

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In 2012, Presto was born within a developer's Facebook team. Because they disagreed with the project's direction, some of its founders decided to start their project; after much negotiation with Facebook, they created Trino, an evolution of Presto.

In addition to Presto and Trino, there are currently Ahana and Starbust that can be deployed and used by Varada:

Trino is a tool designed to query large amounts of data using distributed queries efficiently. If you work with terabytes or petabytes of data, you probably use tools that interact with Hadoop and HDFS. Trino is designed as an alternative to tools that query HDFS using MapReduce job pipelines such as Hive or Pig, but Trino is not limited to accessing HDFS. Trino can be extended to operate on different data sources, including traditional relational databases and other data sources such as Cassandra.

Trino is designed to handle data storage and analysis: analyzing data, aggregating large amounts of data, and producing reports. These workloads are generally classified as Online Analytical Processing (OLAP).

What Trino is not:

Trino is being called a database by many community members, and it makes sense to start with a definition of what Trino is not.

Don’t confuse the fact that Trino understands SQL by providing the capabilities of a standard database. Trino is not a general-purpose relational database. It is not a replacement for databases like MySQL, PostgreSQL, or Oracle. Trino is not designed to handle online transaction processing (OLTP). This is also true for many other databases designed and optimized for data storage or analysis.

Even though Trino is a project created more recently compared to its competitors, it already has a vast range of connectors, “clients”, some business intelligence tools that support it, in addition to having a vast active community and several companies who already use it productively.

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Josue Luzardo Gebrim

As a platform engineer, ecosystems, and data solutions, I'm sharing my opinion and what little I know from time to time here.