Trino: Features, use cases, connectors

Trino Features

Separation of Storage and Compute

With data volumes and types of data increasing on a daily basis, placing this data on a flexible storage medium such as HDFS or a cloud object storage such as Amazon’s S3, S3-compatible stores (Minio, ceph), and Azure’s Blob Storage provides a company with great flexibility on when and where they consume this data. Architected for separation of storage and compute, Trino can scale up and down based on your analytics demand to access this data.

Storage & Compute Separation

Interactive Analytics

From the beginning Trino, formerly PrestoSQL, was designed with SQL query performance in mind. It leverages both well-known and novel techniques for distributed query processing. Some include In-memory parallel processing, Pipelined execution across nodes in the cluster, Multithreaded execution model to keep all the CPU cores busy, Efficient flat-memory data structures to minimize Java garbage collection, and Java Byte code generation. This translates to faster insights into your data at a fraction of the cost of other solutions.

Related reading: Cost-based Query Optimization White Paper

Analyze Anything

Allow your business intelligence users and data scientists to use their favorite tools (Tableau, Qlik, Apache Superset) to access and analyze virtually any data source via Trino. Analyze data from HDFS, object stores, RDBMS (SQL Server, Oracle, MySQL, PostgreSQL), Kafka, MongoDB, and many others. Trino’s flexible architecture allows one perform analytics federated across multiple data sources at the same time. Easily combine historical data from HDFS or objects stores with most recent incoming data from Kafka in the same query.

Secure Everything

Have peace of mind that your data is safe and secure. Starburst Enterprise will fully integrate with your Kerberos and LDAP environments. Further control authorized access to pieces of your data by leveraging AWS & Azure Access management, Hive Metastore Authorization, Apache Sentry Integration, and Apache Ranger integration. For complete security, Starburst Enterprise will support data encryption at-rest and in-transit.

Related reading: Starburst Global Security Webcast

Deploy Anywhere

The separation of storage and compute allows Trino flexible deployment options. Deploy on public clouds such as AWS and Azure, private clouds such as OpenStack, on premises on bare metal commodity hardware or in a virtualized environment. ware on premises. Or let us deploy and manage with our fully managed Trino offering.

Use Cases

Trino can be deployed in many different platforms and locations. Whether in the cloud or on-premises, the technology is truly platform agnostic. Today, companies are using Trino in a variety of ways — for single reporting applications, as a single enterprise-wide query engine, and much more. With the tremendous growth of cloud computing and self-service BI demand, Trino can offer a more agile approach to data access by data consumers.

Allowing data to be consumed by anyone that needs access has become increasingly important to organizations, along with the time it takes to make said data available. In fact, these time metrics have become critical to the success of company departments, whether they are looking at IoT data or providing customers with important buying decision data.

Trino provides a quick and easy way to allow access to data from a variety of sources using industry standard SQL query language. Further, end users don’t have to learn any new complex language or new tool; they can simply utilize existing tools with which they are comfortable.

Trino Connectors

Trino comes with a number of built-in connectors for a variety of data sources. Trino architecture fully abstracts the data sources it can connect to which facilitates the separation of compute and storage. The Connector SPI allows building plugins for file systems and object stores, NoSQL stores, relational database systems, and custom services. As long as one can map the data into relational concepts such as tables, columns, and rows, it is possible to create a Trino connector. What is more, inside a single installation of Trino users can register multiple catalogs and run queries that access data from multiple connectors at once. There is no need to perform a lengthy ETL process since Trino can simply query data where it lives. 

Start Free with
Starburst Galaxy

Up to $500 in usage credits included

  • Query your data lake fast with Starburst's best-in-class MPP SQL query engine
  • Get up and running in less than 5 minutes
  • Easily deploy clusters in AWS, Azure and Google Cloud
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