Trino for the Data Lake

What is the Data Lake?

A data lake is a single store of data that can include structured data from relational databases, semi-structured data and unstructured data. It can include raw copies of data from source systems, sensor data, social data and more. The structure of the data is not typically defined when the data is captured. Data is typically dumped into a data lake without much thought about accessing it.

High Performance Analytics using SQL

Trino (formerly known as PrestoSQL) was built by four Facebook engineers to address performance, scalability and extensibility needs for analytics at Facebook. Trino is a distributed SQL query engine designed for efficient, low latency analytics at scale. It emerged from Facebook as a faster and more powerful way to query a very large Hadoop data warehouse than what Hive and other tools could provide. Modern data lakes often use other object storage systems beyond HDFS from cloud providers including Amazon Simple Storage Service (S3), Google Cloud Storage and Microsoft’s Azure Blob Storage. By leveraging connectors to these cloud object stores, Trino is able to query these systems and enable high performance SQL analytics on your data lake no matter where it’s located or however it stores the data.

Trino has become the choice for querying the data lake due to its high performance at scale. Unlike other options available today, Trino’s concurrency is limited only by the size of your cluster which can be scaled up and down as required. Trino also has connectors to the most popular data sources allowing for data federation across multiple data sources, providing the user with a holistic view of their entire data ecosystem. These connectors allow you query the data where it resides, shortening the data pipeline for your organization.

To learn more about Trino, check out our Trino FAQ page.

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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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