Use cases

Примечание

Ниже приведена оригинальная документация Trino. Скоро мы ее переведем на русский язык и дополним полезными примерами.

This section puts Trino into perspective, so that prospective administrators and end users know what to expect from Trino.

What Trino is not

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

Do not mistake the fact that Trino understands SQL with it providing the features 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 was not designed to handle Online Transaction Processing (OLTP). This is also true for many other databases designed and optimized for data warehousing or analytics.

What Trino is

Trino is a tool designed to efficiently query vast amounts of data using distributed queries. If you work with terabytes or petabytes of data, you are likely using tools that interact with Hadoop and HDFS. Trino was designed as an alternative to tools that query HDFS using pipelines of MapReduce jobs, such as Hive or Pig, but Trino is not limited to accessing HDFS. Trino can be and has been extended to operate over different kinds of data sources, including traditional relational databases and other data sources such as Cassandra.

Trino was designed to handle data warehousing and analytics: data analysis, aggregating large amounts of data and producing reports. These workloads are often classified as Online Analytical Processing (OLAP).