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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM Analytics Engine

    Score7.1 out of 10
    N/AIBM BigInsights is an analytics and data visualization tool leveraging hadoop.N/A

    Presto

    Score2.6 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
    Pricing
    IBM Analytics EnginePresto
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM Analytics EnginePresto
    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
    IBM Analytics EnginePresto
    Small Businesses
    No answers on this topic
    SingleStore
    Score7.5 out of 10
    Medium-sized Companies
    Cloudera Manager
    Score9.9 out of 10
    SAP HANA Cloud
    Score8.9 out of 10
    Enterprises
    Apache Spark
    Score9.2 out of 10
    SAP IQ
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM Analytics EnginePresto
    Likelihood to Recommend
    9.5
    (9 ratings)
    7.8
    (2 ratings)
    User Testimonials
    IBM Analytics EnginePresto
    Likelihood to Recommend
    IBM
    • Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster.
    • But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion.
    Incentivized
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    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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    Pros
    IBM
    • Jobs with Spark, Hadoop, or Hive queries are rapidly attained
    • Can collect, organize and analyze your data accurately
    • You can customize, for example, Spark or Hadoop configuration settings, or Python, R, Scala, or Java libraries.
    Incentivized
    Read full review
    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
    Read full review
    Cons
    IBM
    • Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration.
    • Bundling of the Cloud Object Storage should be included with the Analytics Engine.
    • The inability to add your own Hadoop stack components has made some transfers a little more complex.
    Incentivized
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    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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    Alternatives Considered
    IBM
    We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.
    Incentivized
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    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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    Return on Investment
    IBM
    • This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place.
    • IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI.
    • The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners.
    Incentivized
    Read full review
    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
    Read full review
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