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- With Presto, how it works is you can query data where it lives across many different data sources such as HDFS, MySQL, Cassandra, or Hive. Presto is built on Java and can also integrate with other third-party data sources or infrastructure components.
community.ibm.com/community/user/watsonx/blogs/divya-lokesh/2024/04/12/what-is-presto-and-how-does-it-work
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.
Jan 3, 2023 · ‘Presto (Trino) is a distributed SQL query engine designed to query large sets of data distributed across one or more heterogeneous data sources.’. However, if we talk about exploring the...
Mar 18, 2024 · Presto can connect to a variety of data sources, such as distributed file systems (like HDFS), relational databases, and even cloud storage services. This capability enables users to perform queries on data from heterogeneous sources, without the need to first move or transform the data.
Presto is an open source, distributed SQL query engine designed for fast, interactive queries on data in HDFS, and others. Unlike Hadoop/HDFS, it does not have its own storage system. Thus, Presto is complimentary to Hadoop, with organizations adopting both to solve a broader business challenge.
Apr 12, 2024 · With Presto, how it works is you can query data where it lives across many different data sources such as HDFS, MySQL, Cassandra, or Hive. Presto is built on Java and can also integrate with other third-party data sources or infrastructure components.
Jan 14, 2023 · Presto (or PrestoDB) is a distributed, fast, reliable SQL Query Engine that fetches data from heterogeneous data sources querying large sets((TB, PB) of data and processes in memory. it...
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Dec 21, 2022 · By extending SQL throughout the data analytics ecosystem, Presto helps to democratize the analytics process, enabling more people who rely on data for their work to query the data for answers.
