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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    PrestoDB (or Presto)

    Score10 out of 10
    N/APresto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases. Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.N/A

    Valentina

    Score7 out of 10
    N/AValentina is a relational database software solution offered by Paradigma Software.N/A
    Pricing
    PrestoDB (or Presto)Valentina
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    PrestoDB (or Presto)Valentina
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Best Alternatives
    PrestoDB (or Presto)Valentina
    Small Businesses
    Amazon RDS
    Score8.1 out of 10
    Amazon RDS
    Score8.1 out of 10
    Medium-sized Companies
    SingleStore
    Score8.2 out of 10
    SingleStore
    Score8.2 out of 10
    Enterprises
    SAP IQ
    Score5.4 out of 10
    SAP IQ
    Score5.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    PrestoDB (or Presto)Valentina
    Likelihood to Recommend
    7.8
    (2 ratings)
    7.0
    (1 ratings)
    User Testimonials
    PrestoDB (or Presto)Valentina
    Likelihood to Recommend
    Open Source
    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
    Incentivized
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    Paradigma Software
    If you have to manage a lot of different databases from different vendors, you could do well by standardizing on this product. It checks all the boxes for a proper database management studio. You would only have to learn one product to manage them all. However, if you are looking to find a good product for a single database vendor, you might be better off finding a tool that was designed specifically for that vendor product.
    Incentivized
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    Pros
    Open Source
    • 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.
    Incentivized
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    Paradigma Software
    • Foreign Key Constraint data viewer! This was a tremendously helpful feature that not many other products have. Just pick a constraint and see the data in the child tables! No setup required!
    • Supports any and every database imaginable.
    Incentivized
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    Cons
    Open Source
    • 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.
    Incentivized
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    Paradigma Software
    • Somewhat laggy performance. Boot up speed was on the slow side and connecting to our database servers was also a little slower than other products.
    • User interface can be a little clunky. Instead of the usual tree view of servers, databases, and schemas, you are presented with lists that you click on and get new windows to pick the new list of data from. Not organized efficiently.
    Incentivized
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    Alternatives Considered
    Open Source
    Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.
    Incentivized
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    Paradigma Software
    Compared to Microsoft's SQL Management Studio, Valentina studio was comparable, just harder to get used to in the UI department. It ran slightly slower than other products but did save some time with neat features they baked into the product. However, in using DBeaver Community and DBForge Studio for PostgreSQL from Devart, we found different products that the team ultimately decided to use. DBeaver has all of the features we needed most (minus the constraint data viewer) and a more intuitive UI that we were used to. DBForge Studio for PostgreSQL has a very standard Windows look and feel and lacks some features, like database/table designers, but makes up for those shortcomings in the much easier filtering and sorting options right in the data grids. You can even write a query and edit the data returned, which is something we don't see in many of these tools. Our team ultimately settled on the developers using DBeaver and the support team that needs data viewing/editing capabilities using DBForge Studio.
    Incentivized
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    Return on Investment
    Open Source
    • 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.
    Incentivized
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    Paradigma Software
    • It saved time in some areas of finding child data by not having to write queries to find it.
    • The user interface caused some extra training for some users and ultimately caused them to not like using it.
    Incentivized
    Read full review
    ScreenShots