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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    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

    Workato

    Score9.3 out of 10
    N/AWorkato is a cloud or on-premise automation and integration platform with enterprise-grade capabilities and no coding required. Workato provides pre-built connectors to integrate with over 300 business applications and enables task automation across apps.N/A
    Pricing
    TensorFlowWorkato
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    TensorFlowWorkato
    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
    Community Pulse
    TensorFlowWorkato
    Considered Both Products
    Open Source
    No answer on this topic
    Workato
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    57%
    Would buy again
    4 Answers
    Delivers good value for the price
    No answers on this topic
    50%
    Delivers good value for the price
    3 Answers
    Happy with the feature set
    No answers on this topic
    71%
    Happy with the feature set
    5 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    67%
    Lived up to sales and marketing promises
    4 Answers
    Implementation went as expected
    No answers on this topic
    86%
    Implementation went as expected
    6 Answers
    Features
    TensorFlowWorkato
    Cloud Data Integration
    Comparison of Cloud Data Integration features of TensorFlow and Workato
    Feature
    TensorFlow
    -
    Ratings
    Workato
    8.0
    38 Ratings
    1% below category average
    Pre-built connectors00 Ratings10.038 Ratings
    Connector modification00 Ratings10.036 Ratings
    Support for real-time and batch integration00 Ratings5.034 Ratings
    Data quality services00 Ratings6.031 Ratings
    Data security features00 Ratings9.034 Ratings
    Monitoring console00 Ratings8.038 Ratings
    Best Alternatives
    TensorFlowWorkato
    Small Businesses
    Google Cloud AI
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    Make
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    Medium-sized Companies
    Google Cloud AI
    Score8.7 out of 10
    IBM App Connect
    Score9 out of 10
    Enterprises
    Google Cloud AI
    Score8.7 out of 10
    TIBCO Integration (including BusinessWorks and Flogo)
    Score8.9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    TensorFlowWorkato
    Likelihood to Recommend
    6.0
    (15 ratings)
    9.0
    (38 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    1.0
    (3 ratings)
    Usability
    9.0
    (1 ratings)
    9.0
    (4 ratings)
    Support Rating
    9.1
    (2 ratings)
    8.0
    (6 ratings)
    Implementation Rating
    8.0
    (1 ratings)
    3.0
    (1 ratings)
    User Testimonials
    TensorFlowWorkato
    Likelihood to Recommend
    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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    Workato
    Workato is brilliant to make separate applications work together without much effort or specialists being needed. When specific events on software A should trigger actions on B (or more) and you want that to happen without any development or big budgets, that's where Workato comes into play. It's a great help if you want tasks automated, communications flowing and data synced between different applications.
    Read full review
    Pros
    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
    Read full review
    Workato
    • The Workato product interface is brilliantly thought through and designed. The learning curve for first timers is easy enough to get started and build useful things, and Workato really shines in their ability to handle complex triggers and interactions. Workato allows people to build software apps so much faster than by coding each functionality.
    • Workato has fantastic documentation, making things accessible without any holes in the product. The product just works, never has any bugs, never lags, and just generally allows us to see and change exactly what we need to.
    • Workato has an absolutely amazing support team. We tried the free version for a while, then realized it was the single most important software tool we have, and we upgraded. The support at the paid tier is A+, seriously the best from any company we've worked with. Feels more like a good friend then a support rep.
    Read full review
    Cons
    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
    Workato
    • Customer support - responsive, but often not equipped to help efficiently identify root cause of issue. Need to improve escalation to technical resources and turnaround time
    • Recipe organization and sharing. Can be challenging to copy recipes, or grab recipes from publicly available site. There are often dependencies and errors that have vague descriptions.
    Incentivized
    Read full review
    Likelihood to Renew
    Open Source
    No answers on this topic
    Workato
    We need to develop Enterprise Application Integrations and Workato was not designed for this
    Read full review
    Usability
    Open Source
    Support of multiple components and ease of development.
    Incentivized
    Read full review
    Workato
    The sheer work Workato eliminates from people's daily jobs is simply a great contribution to people's productivity and a boost to capability. It actually strikes the balance between business and tech teams. It also reduces dependency on developers, and speeds up their delivery too. The only reason it's not a full 10/10 is for the price - it's a bit expensive for what we'd like, and their batch or high data volume processing can be improved.
    Read full review
    Support Rating
    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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    Workato
    They employ an extremely knowledgeable team of problem solvers. I've never had a disappointing interaction or one that has left me still searching for answers. I know that when I ask for help, they'll partner with me until we find a solution together
    Incentivized
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    Implementation Rating
    Open Source
    Use of cloud for better execution power is recommended.
    Incentivized
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    Workato
    We discovered that we could not use Workato for our more complex, large enterprise integrations. It was useful for simple workflows that matched the prebuilt recipes.
    Read full review
    Alternatives Considered
    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
    Read full review
    Workato
    We already used Zapier, but since it doesn't support NetSuite we had to choose another automation platform. Now that we've been using Workato for a few months, we have plans to move the stuff we're going through Zapier to Workato. We set up a trial account with all the other platforms, and they were all more expensive and A LOT more complicated than Workato.
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    Return on Investment
    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
    Workato
    • As business consultants, Workato has greatly improved our offerings to our clients as well as improved the time frame to implement automated workflows and integrations.
    • For our clients, the return on investment is almost immediate. Once a Workato recipe is up and running (which can be done very fast), data is integrating, duplicate data entry and user errors are eliminated, and cross-company KPI metrics are easier to report than ever.
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