Apache Drill vs Presto

May 25, 2023 | Author: Michael Stromann
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Apache Drill
Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage. Get faster insights without the overhead (data loading, schema creation and maintenance, transformations, etc.). Analyze the multi-structured and nested data in non-relational datastores directly without transforming or restricting the data
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Presto
Presto is a highly parallel and distributed query engine for big data, that is built from the ground up for efficient, low latency analytics.
Apache Drill and Presto are both distributed query engines designed for querying large-scale data sets across various data sources, but they have different approaches and characteristics. Apache Drill focuses on providing a schema-free, self-describing data exploration experience, allowing users to query structured and semi-structured data using standard SQL queries. It offers a flexible, schema-on-read approach that enables querying diverse data sources with ease, including files, databases, and NoSQL systems. Presto, on the other hand, is optimized for high-performance interactive queries and is widely used for data analysis and exploration. It supports various data sources and provides advanced features like distributed SQL queries, query optimization, and query federation across multiple data platforms.

See also: Top 10 Big Data platforms
Apache Drill vs Presto in our news:

2019. Starburst raises $22M to modernize data analytics with Presto



Starburst, the company seeking to commercialize the open-source Presto distributed query engine for big data (originally developed at Facebook), has announced a successful funding round, raising $22 million. The primary objective of Presto is to enable anyone to utilize the standard SQL query language for executing interactive queries on vast amounts of data stored across diverse sources. Starburst intends to monetize Presto by introducing several enterprise-oriented features. These additions will primarily focus on enhancing security, such as role-based access control, and integrating connectors to enterprise systems like Teradata, Snowflake, and DB2. Additionally, Starburst plans to provide a management console that empowers users to configure the cluster for automatic scaling, among other functionalities.

Author: Michael Stromann
Michael is an expert in IT Service Management, IT Security and software development. With his extensive experience as a software developer and active involvement in multiple ERP implementation projects, Michael brings a wealth of practical knowledge to his writings. Having previously worked at SAP, he has honed his expertise and gained a deep understanding of software development and implementation processes. Currently, as a freelance developer, Michael continues to contribute to the IT community by sharing his insights through guest articles published on several IT portals. You can contact Michael by email stromann@liventerprise.com