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PrestoDB (or Presto) vs. Talend Data Fabric

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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

    Talend Data Fabric

    Score10 out of 10
    N/AThe Talend Data Fabric helps organizations to achieve and maintain complete, trustworthy, and uncompromised data, so that they can stay in control, mitigate risk, and drive value.N/A
    Pricing
    PrestoDB (or Presto)Talend Data Fabric
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    PrestoDB (or Presto)Talend Data Fabric
    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)Talend Data Fabric
    Small Businesses
    Amazon RDS
    Score8.1 out of 10
    No answers on this topic
    Medium-sized Companies
    SingleStore
    Score8.2 out of 10
    SAP Datasphere
    Score8.6 out of 10
    Enterprises
    SAP IQ
    Score5.4 out of 10
    SAP Datasphere
    Score8.6 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    PrestoDB (or Presto)Talend Data Fabric
    Likelihood to Recommend
    7.8
    (2 ratings)
    9.6
    (7 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    8.0
    (1 ratings)
    Usability
    -
    (0 ratings)
    7.0
    (1 ratings)
    Support Rating
    -
    (0 ratings)
    10.0
    (1 ratings)
    User Testimonials
    PrestoDB (or Presto)Talend Data Fabric
    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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    Qlik
    Truly trusted contact center where the effective solution is always guaranteed. It is not a one-off fix to a specific data integration or management problem. It is a permanent and scalable solution to manage all of your data under a unified environment. Easy to use, great performance, used it for our internal data warehouse. Easy to build and connect to our data sources such as Salesforce, Netsuite, and Marketo.
    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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    Qlik
    • It supports a wide variety of connectors (Systems/endpoints)
    • It provides great flexibility for developers as it not only has a lot of predefined ready to use the function but also provides the ability to use complex java code within the platform. Great tool if you have good developers available.
    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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    Qlik
    • The print and export functionality are missing in the Community version which frustrates a lot of our clients as well as internal users.
    • The learning curve is very steep for all Talend products including DQ.
    • Lack of easy to create workflows for jobs that can be repeated.
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    Likelihood to Renew
    Open Source
    No answers on this topic
    Qlik
    Lack of report export and publication! Steep learning curve!
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    Usability
    Open Source
    No answers on this topic
    Qlik
    At this moment the usability of Talend Data Quality is optimal, too bad I cannot say the same in the first three months, it was always a problem due to its steep learning curve, but what matters is being able to use it effectively at this precise moment.
    Incentivized
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    Support Rating
    Open Source
    No answers on this topic
    Qlik
    Talend Data Quality gave us direct help in the learning process and prevented us from taking many more months to adapt and I appreciate this from the heart, I think that thanks to the support we can have very detailed reports that help increase the use of Talend Data Quality in the company.
    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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    Qlik
    The engine with which it works to process a lot of information is striking, the comparison also being the connectors it has for different RDBMS, which other tools do not count as they are GNU licenses or community editions. The friendly and intuitive environment is what catches the eye. that's why I choose Talend over any other tool
    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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    Qlik
    • Definitely simplified the development efforts on our end in doing the data integration, saving lots of human hours.
    • Small company, so cost could be a problem for these services, but works so far.
    Incentivized
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