TrustRadius: an HG Insights company

Save this comparison

Save this comparison

Add Product

Recommended Comparisons

    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Eclipse

    Score8.3 out of 10
    N/AEclipse is a free and open source integrated development environment (IDE).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
    EclipseTensorFlow
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    EclipseTensorFlow
    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
    EclipseTensorFlow
    Considered Both Products
    Open Source
    No answer on this topic
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
    94%
    Would buy again
    29 Answers
    No answers on this topic
    Delivers good value for the price
    97%
    Delivers good value for the price
    29 Answers
    No answers on this topic
    Happy with the feature set
    94%
    Happy with the feature set
    29 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    95%
    Lived up to sales and marketing promises
    21 Answers
    No answers on this topic
    Implementation went as expected
    96%
    Implementation went as expected
    24 Answers
    No answers on this topic
    Best Alternatives
    EclipseTensorFlow
    Small Businesses
    No answers on this topic
    Google Cloud AI
    Score8.7 out of 10
    Medium-sized Companies
    No answers on this topic
    Google Cloud AI
    Score8.7 out of 10
    Enterprises
    No answers on this topic
    Google Cloud AI
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    EclipseTensorFlow
    Likelihood to Recommend
    9.9
    (74 ratings)
    6.0
    (15 ratings)
    Likelihood to Renew
    9.0
    (1 ratings)
    -
    (0 ratings)
    Usability
    8.0
    (3 ratings)
    9.0
    (1 ratings)
    Support Rating
    6.8
    (19 ratings)
    9.1
    (2 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.0
    (1 ratings)
    User Testimonials
    EclipseTensorFlow
    Likelihood to Recommend
    Open Source
    I think that if someone asked me for an IDE for Java programming, I would definitely recommend Eclipse as is one of the most complete solutions for this language out there. If the main programming language of that person is not Java, I don't think Eclipse would suit his needs[.]
    Incentivized
    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
    Read full review
    Pros
    Open Source
    • Eclipse organizes imports well and does a good job presenting different programming languages.
    • Eclipse auto formats source code allowing customization and increased readability.
    • Eclipse reports errors automatically to users rather than logging it to the console.
    • Eclipse has coding shortcuts and auto-correction features allowing faster software development.
    Incentivized
    Read full review
    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
    Cons
    Open Source
    • While the DB integration is broad (many connectors) it isn't particularly deep. So if you need to do serious DB work on (for example) SQL Server, it is sometimes necessary to go directly to the SQL Server Studio. But for general access and manipulation, it is ok.
    • The syntax formatting is sometimes painful to set up and doesn't always support things well. For example, it doesn't effectively support SCSS.
    • Using it for remote debugging in a VM works pretty well, but it is difficult to set up and there is no documentation I could find to really explain how to do it. When remote debugging, the editor does not necessarily integrate the remote context. So, for example, things like Pylint don't always find the libraries in the VM and display spurious errors.
    • The debugging console is not the default, and my choice is never remembered, so every time I restart my program, it's a dialog and several clicks to get it back. The debugging console has the same contextual problems with remote debugging that the editor does.
    Incentivized
    Read full review
    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
    Open Source
    I love this product, what makes it one of the best tool out in the market is its ability to function with a wide range of languages. The online community support is superb, so you are never stuck on an issue. The customization is endless, you can keep adding plugins or jars for more functionalities as per your requirements. It's Free !!!
    Incentivized
    Read full review
    Open Source
    No answers on this topic
    Usability
    Open Source
    It has everything that the developer needs to do the job. Few things that I have used in my day-to-day development 1. Console output. 2. Software flash functionality supporting multiple JTAG vendors like J-LINK. 3. Debugging capabilities like having a breakpoint, looking at the assembly, looking at the memory etc. this also applies to Embedded boards. 4. Plug-in like CMake, Doxygen and PlantUML are available.
    Incentivized
    Read full review
    Open Source
    Support of multiple components and ease of development.
    Incentivized
    Read full review
    Support Rating
    Open Source
    I gave this rating because Eclipse is an open-source free IDE therefore no support system is available as far as I know. I have to go through other sources to solve my problem which is very tough and annoying. So if you are using Eclipse then you are on your own, as a student, it is not a big issue for me but for developers it is a need.
    Read full review
    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
    Read full review
    Implementation Rating
    Open Source
    No answers on this topic
    Open Source
    Use of cloud for better execution power is recommended.
    Incentivized
    Read full review
    Alternatives Considered
    Open Source
    The installation, adaptability, and ease of usage for Eclipse are pretty high and simple compared to some of the other products. Also, the fact that it is almost a plug and play once the connections are established and once a new user gets the hang of the system comes pretty handy.
    Incentivized
    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
    Read full review
    Return on Investment
    Open Source
    • This development environment offers the possibility of improving the productivity time of work teams by supporting the integration of large architectures.
    • It drives constant change and evolution in work teams thanks to its constant versioning.
    • It works well enough to develop continuous server client integrations, based on solid or any other programming principle.
    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