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Presto is an open source SQL query engine supported by Teradata designed to run queries on data stored in Hadoop or in traditional databases. Teradata's development of Presto followed the acquisition of Hadapt and Revelytix.Why do we PrestoPresto is used at Uuber for ad-hoc querying on datasets and also for a few data driven applications. It is used across the entire organization to make data driven decisions, reporting, experimentation analysis etc. Presto provides a scalable, fast distributed query engine and we use it on top of HDFS.,Fast - Presto, is incredibly fast due to its optimized query engine and is well suited for interactive analysis. Flexible - Presto is highly flexible as it operates with a plug and play model for data sources. Joining and query across different data sources is very easy with presto (eg. HDFS, MySQL, Kafka). ANSI Sql - Presto follows ANSI SQL which is the recognized SQL language and hence helps allow easy query migration without much overhead. Large Fact + Small Dimension table joins made fast - By design presto excels most distributed query engines out there in this type of queries.,Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem. Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override. UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.,8,Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica. Presto has helped build data driven applications on its stack than maintain a separate online/offline stack. Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.,Vertica, Apache Spark and Apache Pig,Vertica, Apache Hive, Apache PigPresto Review for Insider (Gannett)Presto is used as our story publisher via The Des Moines Register and Gannett sites. We build, edit, and design story layout and publish to our website. My Marketing Group mainly uses Presto for our Insider program - this is a template of offers, deals & events exclusively for our subscribers.,Linking, embedding links and adding images is easy enough. Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope). Organizing & design is fairly simple with click & drag parameters.,HCI - Intuitively there are quite a few design elements I was unsure of before I got enough practice. Curating Fronts - should have an auto-organize element so you don't need to move each front. Save, Publish & Unpublish options should be easier to understand. Presto should have a copy feature.,7,Our Insider program continues to grow - Presto is definitely not a hinderance. Gannett corporate pays for the Presto services for all of the Gannett Newspaper sites - i have no input on ROI. We do not use Presto to gain NEW subscribers.,Adobe Photoshop and ION,Adobe Photoshop
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Presto
8 Ratings
Score 7.5 out of 101
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Presto Reviews

Presto
8 Ratings
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Score 7.5 out of 101
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Praveen Murugesan profile photo
August 08, 2017

User Review: "Why do we Presto"

Score 8 out of 10
Vetted Review
Verified User
Review Source
Presto is used at Uuber for ad-hoc querying on datasets and also for a few data driven applications. It is used across the entire organization to make data driven decisions, reporting, experimentation analysis etc. Presto provides a scalable, fast distributed query engine and we use it on top of HDFS.
  • Fast - Presto, is incredibly fast due to its optimized query engine and is well suited for interactive analysis.
  • Flexible - Presto is highly flexible as it operates with a plug and play model for data sources. Joining and query across different data sources is very easy with presto (eg. HDFS, MySQL, Kafka).
  • ANSI Sql - Presto follows ANSI SQL which is the recognized SQL language and hence helps allow easy query migration without much overhead.
  • Large Fact + Small Dimension table joins made fast - By design presto excels most distributed query engines out there in this type of queries.
  • Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
  • Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
  • UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica.
Read Praveen Murugesan's full review
Corinne Nacin-Martinez profile photo
March 23, 2017

"Presto Review for Insider (Gannett)"

Score 7 out of 10
Vetted Review
Verified User
Review Source
Presto is used as our story publisher via The Des Moines Register and Gannett sites. We build, edit, and design story layout and publish to our website. My Marketing Group mainly uses Presto for our Insider program - this is a template of offers, deals & events exclusively for our subscribers.
  • Linking, embedding links and adding images is easy enough.
  • Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
  • Organizing & design is fairly simple with click & drag parameters.
  • HCI - Intuitively there are quite a few design elements I was unsure of before I got enough practice.
  • Curating Fronts - should have an auto-organize element so you don't need to move each front.
  • Save, Publish & Unpublish options should be easier to understand.
  • Presto should have a copy feature.
Simple stories & templates work nicely - like for our Insider program.

Stories that include a lot of images may be challenging to create & have look appealing.
Read Corinne Nacin-Martinez's full review

Presto Scorecard Summary

About Presto

Presto is an open source SQL query engine supported by Teradata designed to run queries on data stored in Hadoop or in traditional databases. Teradata's development of Presto followed the acquisition of Hadapt and Revelytix.

Presto Technical Details

Operating Systems: Unspecified
Mobile Application:No