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1. www.eecs.umich.edu › papers › prestoPresto: A Decade of SQL Analytics at Meta

   www.eecs.umich.edu › papers › presto

   ABSTRACT. Presto is an open-source distributed SQL query engine that sup-ports analytics workloads involving multiple exabyte-scale data sources. Presto is used for low-latency interactive use cases as well as long-running ETL jobs at Meta.

2. robots.net › fintech › what-is-presto-in-big-dataWhat Is Presto In Big Data - Robots.net

   robots.net › fintech › what-is-presto-in-big-data

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   Nov 16, 2023 · Compatibility: Presto’s wide compatibility with different data sources and formats allows organizations to work with heterogeneous data ecosystems. Whether it’s traditional relational databases, data warehouses, or distributed file systems, Presto can seamlessly connect to and query data stored in these systems.

3. trino.io › Presto_SQL_on_EverythingPresto: SQL on Everything - Trino

   trino.io › Presto_SQL_on_Everything

   Presto is designed to be adaptive, flexible, and extensible. It provides an ANSI SQL interface to query data stored in Hadoop environments, open-source and proprietary RDBMSs, NoSQL systems, and stream processing systems such as Kafka.

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4. indico.cern.ch › Introduction_to_PrestoEvaluation of Presto for integrating databases and big data ...

   indico.cern.ch › Introduction_to_Presto

   •Presto –distributed SQL engine on multiple pluggable data stores •Excels on low latency query executions, not for batch processing •With single JDBC client you can write and read into big data stores

5. arxiv.org › pdf › 2304An Empirical Evaluation of Columnar Storage Formats (Extended ...

   arxiv.org › pdf › 2304

   In the early 2010s, organizations developed data processing engines for the open-source big data ecosystem [12], including Hive [13, 110], Impala [16], Spark [20, 118], and Presto [19, 103], to respond to the petabytes of data generated per day and the growing demand for large-scale data analytics. To facilitate data sharing across the vari-

6. dl.acm.org › doi › 10Presto: A Decade of SQL Analytics at Meta | Proceedings of ...

   dl.acm.org › doi › 10

   Jun 20, 2023 · Presto is an open-source distributed SQL query engine that supports analytics workloads involving multiple exabyte-scale data sources. Presto is used for low-latency interactive use cases as well as long-running ETL jobs at Meta.

7. People also ask

   Does Presto work with heterogeneous data ecosystems?

   • Compatibility: Presto’s wide compatibility with different data sources and formats allows organizations to work with heterogeneous data ecosystems. Whether it’s traditional relational databases, data warehouses, or distributed file systems, Presto can seamlessly connect to and query data stored in these systems.

   What Is Presto In Big Data - Robots.net

   robots.net/fintech/what-is-presto-in-big-data/

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   What is Presto & how does it work?

   • Presto is an open-source distributed SQL query engine that supports analytics workloads involving multiple exabyte-scale data sources. Presto is used for low-latency interactive use cases as well as long-running ETL jobs at Meta. It was originally launched at Meta in 2013 and donated to the Linux Foundation in 2019.

   Presto: A Decade of SQL Analytics at Meta | Proceedings of the ACM on

   dl.acm.org/doi/10.1145/3589769

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   Is Presto a legacy query engine?

   • Some of the notable ones are hierarchical caching, native vectorized execution engines, materialized views, and Presto on Spark. With these new capabilities, we have deprecated or are in the process of deprecating various legacy query engines so that Presto becomes the single piece for the entire data warehouse.

   Presto: A Decade of SQL Analytics at Meta | Proceedings of the ACM on

   dl.acm.org/doi/10.1145/3589769

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   Does Presto support mutable data?

   • Data warehouses historically only support immutable data. In re-cent years, we have seen an increasing trend of mutable data sup-port with versioning. Examples are Delta Lake , Iceberg , and Hudi . Presto integrates with all these table formats. However, they are not suficient for use cases within Meta.

   Presto: A Decade of SQL Analytics at Meta

   www.eecs.umich.edu/courses/eecs584/static_files/papers/presto.pdf

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   Is Presto a good solution for big data analytics?

   • With ongoing development and support, Presto is poised to remain a leading solution for real-time analytics in the world of big data. Presto offers a wide range of features that make it a powerful and versatile tool for big data analytics. These features contribute to its popularity and adoption in various industries.

   What Is Presto In Big Data - Robots.net

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   What makes Presto unique?

   • Community and Ecosystem: Presto benefits from a vibrant and active community of developers and users who contribute to its development and support its adoption. This community-driven approach ensures frequent updates, bug fixes, and enhancements, keeping Presto at the forefront of big data analytics.

   What Is Presto In Big Data - Robots.net

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8. www.semanticscholar.org › paper › Presto:-SQL-on[PDF] Presto: SQL on Everything | Semantic Scholar

   www.semanticscholar.org › paper › Presto:-SQL-on

   Apr 8, 2019 · Presto's Connector API allows plugins to provide a high performance I/O interface to dozens of data sources, including Hadoop data warehouses, RDBMSs, NoSQL systems, and stream processing systems. In this paper, we outline a selection of use cases that Presto supports at Facebook.