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      • Presto allows engineers to analyze how Facebook's products are used and to make predictions based on that data. In 2013, Facebook made Presto publicly available as open source software to give outside people and companies access to it.
  1. How does Presto work? Presto is a distributed system that runs on Hadoop, and uses an architecture similar to a classic massively parallel processing (MPP) database management system. It has one coordinator node working in synch with multiple worker nodes.

  2. Apr 12, 2024 · How does PrestoDB work? PrestoDB is an open-source distributed SQL query engine for running interactive analytic queries against all types of data sources. It enables self-service ad-hoc analytics on large amounts of data.

  3. Nov 16, 2023 · Presto is a cutting-edge open-source distributed SQL query engine designed for high-performance analytics on big data. It was developed by Facebook and has gained widespread adoption in the tech industry due to its speed, flexibility, and scalability.

  4. Nov 6, 2013 · Presto is a distributed SQL query engine optimized for ad-hoc analysis at interactive speed. It supports standard ANSI SQL, including complex queries, aggregations, joins, and window functions. The diagram below shows the simplified system architecture of Presto. The client sends SQL to the Presto coordinator.

  5. May 23, 2019 · Facebook Presto Data Visualization, Reporting, and Analytics Support is gaining tracking for the query engine across a wide variety of data visualization and business intelligence tools. Today, there are several options available to analysts for tapping into your data via Presto.

    • Thomas Spicer
  6. Apr 12, 2019 · Presto is an open source distributed query engine that supports much of the SQL analytics workload at Facebook. Presto is designed to be adaptive, flexible, and extensible. It supports a wide variety of use cases with diverse characteristics.

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  8. Dec 3, 2020 · “ Presto (or PrestoDB) is an open source, distributed SQL query engine, designed from the ground up for fast analytic queries against data of any size.” It interfaces both non-relational data sources like Amazon S3 and Hadoop HDFS, MongoDB, and HBase, as well as relational databases like MySQL, PostgreSQL, and MS SQL Server.

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