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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Datameer

    Score8.4 out of 10
    N/ADatameer helps businesses clean up, combine, and organize data to make sense of it and use it for reports and machine learning.N/A

    TensorFlow

    Score7.6 out of 10
    N/ATensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.N/A
    Pricing
    DatameerTensorFlow
    Editions & Modules
    Team/Enterprise
    Contact for pricing
    per month Team
    No answers on this topic
    Offerings
    Pricing Offerings
    DatameerTensorFlow
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Best Alternatives
    DatameerTensorFlow
    Small Businesses
    No answers on this topic
    Google Cloud AI
    Score8.7 out of 10
    Medium-sized Companies
    Toad Data Point
    Score8.4 out of 10
    Google Cloud AI
    Score8.7 out of 10
    Enterprises
    AWS Glue
    Score8.8 out of 10
    Google Cloud AI
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    DatameerTensorFlow
    Likelihood to Recommend
    9.0
    (9 ratings)
    6.0
    (15 ratings)
    Likelihood to Renew
    6.4
    (7 ratings)
    -
    (0 ratings)
    Usability
    9.0
    (1 ratings)
    9.0
    (1 ratings)
    Support Rating
    8.0
    (1 ratings)
    9.1
    (2 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.0
    (1 ratings)
    User Testimonials
    DatameerTensorFlow
    Likelihood to Recommend
    Datameer
    Datameer is a great tool if someone is capable of keeping the most recent version of the tool up to date along with the most recent version of the distribution of Hadoop. The tool is easy to support but it must have someone who can run the back end processes
    Read full review
    Open Source
    TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
    Incentivized
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    Pros
    Datameer
    • It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT.
    • It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization .
    • Excel feature is awesome for business users which is already provided by Datameer.
    • Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation.
    • Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash.
    • It can be used in premise or in a cloud computing environment.
    • Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem.
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    Open Source
    • A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc.
    • Amazing community helps developers obtain knowledge faster and get unblocked in this active development space.
    • Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models.
    Incentivized
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    Cons
    Datameer
    • Concentration issues are possible while using a lot of tabs at once.
    • In most cases, the length of a tutorial video is excessive.
    • A more condensed design is certainly a viable option.
    Incentivized
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    Open Source
    • RNNs are still a bit lacking, compared to Theano.
    • Cannot handle sequence inputs
    • Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
    Read full review
    Likelihood to Renew
    Datameer
    Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel
    Read full review
    Open Source
    No answers on this topic
    Usability
    Datameer
    Easy to use for most things, starts to require some planning as your projects get more complex.
    Read full review
    Open Source
    Support of multiple components and ease of development.
    Incentivized
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    Support Rating
    Datameer
    No answers on this topic
    Open Source
    Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
    Incentivized
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    Implementation Rating
    Datameer
    No answers on this topic
    Open Source
    Use of cloud for better execution power is recommended.
    Incentivized
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    Alternatives Considered
    Datameer
    Pricing, support, and ease of use. We plan to scale up our data over the net few years and Datameer gives us all the things we need in one tool. Handles large transformations quickly and works with all the cloud data warehouses.
    Datameer's per-user pricing sealed the deal for us as we plan to transfer much more data over the next few years. We looked at Fivetran but the usage pricing discourages growth. We also looked at Informatica but it was too expensive and didn't work as well with other BI tools like Datameer does.
    Read full review
    Open Source
    Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
    Incentivized
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    Return on Investment
    Datameer
    • We have not been able to reach our business objectives just yet.
    • Hadoop its a hard sell in most companies still.
    • Legacy skills are still highly on demand and as long as an easier path leverage SQL for example is available, it would be hard to gain more adoption.
    Incentivized
    Read full review
    Open Source
    • Learning is s bit difficult takes lot of time.
    • Developing or implementing the whole neural network is time consuming with this, as you have to write everything.
    • Once you have learned this, it make your job very easy of getting the good result.
    Incentivized
    Read full review
    ScreenShots

    Datameer Screenshots

    Screenshot of DATA TRANSFORMATION: SQL or No Code

SQL SELECT statements can be used to explore and shape data. Work is represented visually on a canvas like interface, making it easier to design and maintain projects.

Datameer includes library of pre-built drag-and-drop transformations to accelerate SQL development or transform datasets without writing code.Screenshot of DATA CATALOG: Collaboration in Snowflake

Search, Metadata, Data Profiling, and Auto documentationScreenshot of AUTOMATION & INSIGHTS

Insights can be sent to email or Slack, integrated, and deployed to SnowflakeScreenshot of PRODUCTION PIPELINES: From ad-hoc exploration to production pipelines

GIT version control, materialization, dependency management, monitoring