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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Jenkins

    Score8.1 out of 10
    N/AJenkins is an open source automation server. Jenkins provides hundreds of plugins to support building, deploying and automating any project. As an extensible automation server, Jenkins can be used as a simple CI server or turned into a continuous delivery hub for any project.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
    JenkinsTensorFlow
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    JenkinsTensorFlow
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    JenkinsTensorFlow
    Considered Both Products
    Open Source
    No answer on this topic
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
    87%
    Would buy again
    26 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    27 Answers
    No answers on this topic
    Happy with the feature set
    87%
    Happy with the feature set
    26 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    93%
    Lived up to sales and marketing promises
    13 Answers
    No answers on this topic
    Implementation went as expected
    96%
    Implementation went as expected
    22 Answers
    No answers on this topic
    Best Alternatives
    JenkinsTensorFlow
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    Apache Maven
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    Medium-sized Companies
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    Enterprises
    Gradle Build Tool (Open Source)
    Score9 out of 10
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    All AlternativesView all alternativesView all alternatives
    User Ratings
    JenkinsTensorFlow
    Likelihood to Recommend
    6.8
    (74 ratings)
    6.0
    (15 ratings)
    Usability
    6.4
    (8 ratings)
    9.0
    (1 ratings)
    Performance
    8.9
    (6 ratings)
    -
    (0 ratings)
    Support Rating
    6.6
    (6 ratings)
    9.1
    (2 ratings)
    Implementation Rating
    6.0
    (1 ratings)
    8.0
    (1 ratings)
    User Testimonials
    JenkinsTensorFlow
    Likelihood to Recommend
    Open Source
    Jenkins is a highly customizable CI/CD tool with excellent community support. One can use Jenkins to build and deploy monolith services to microservices with ease. It can handle multiple "builds" per agent simultaneously, but the process can be resource hungry, and you need some impressive specs server for that. With Jenkins, you can automate almost any task. Also, as it is an open source, we can save a load of money by not spending on enterprise CI/CD tools.
    Incentivized
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    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
    Open Source
    • Automated Builds: Jenkins is configured to monitor the version control system for new pull requests. Once a pull request is created, Jenkins automatically triggers a build process. It checks out the code, compiles it, and performs any necessary build steps specified in the configuration.
    • Unit Testing: Jenkins runs the suite of unit tests defined for the project. These tests verify the functionality of individual components and catch any regressions or errors. If any unit tests fail, Jenkins marks the build as unsuccessful, and the developer is notified to fix the issues.
    • Code Analysis: Jenkins integrates with code analysis tools like SonarQube or Checkstyle. It analyzes the code for quality, adherence to coding standards, and potential bugs or vulnerabilities. The results are reported back to the developer and the product review team for further inspection.
    Incentivized
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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
    Open Source
    • The UI could be slightly better, it feels kind of like the 90s, but it works well.
    • An easier way to filter jobs other than views on the dashboard.
    • An easier way to read the console logs when tests do fail.
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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.
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    Likelihood to Renew
    Open Source
    We have a certain buy-in as we have made a lot of integrations and useful tools around jenkins, so it would cost us quite some time to change to another tool. Besides that, it is very versatile, and once you have things set up, it feels unnecessary to change tool. It is also a plus that it is open source.
    Incentivized
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    Open Source
    No answers on this topic
    Usability
    Open Source
    Jenkins streamlines development and provides end to end automated integration and deployment. It even supports Docker and Kubernetes using which container instances can be managed effectively. It is easy to add documentation and apply role based access to files and services using Jenkins giving full control to the users. Any deviation can be easily tracked using the audit logs.
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    Open Source
    Support of multiple components and ease of development.
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    Performance
    Open Source
    No, when we integrated this with GitHub, it becomes more easy and smart to manage and control our workforce. Our distributed workforce is now streamlined to a single bucket. All of our codes and production outputs are now automatically synced with all the workers. There are many cases when our in-house team makes changes in the release, our remote workers make another release with other environment variables. So it is better to get all of the work in control.
    Incentivized
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    Open Source
    No answers on this topic
    Support Rating
    Open Source
    As with all open source solutions, the support can be minimal and the information that you can find online can at times be misleading. Support may be one of the only real downsides to the overall software package. The user community can be helpful and is needed as the product is not the most user-friendly thing we have used.
    Incentivized
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    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.
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    Implementation Rating
    Open Source
    It is worth well the time to setup Jenkins in a docker container. It is also well worth to take the time to move any "Jenkins configuration" into Jenkinsfiles and not take shortcuts.
    Incentivized
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    Open Source
    Use of cloud for better execution power is recommended.
    Incentivized
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    Alternatives Considered
    Open Source
    Overall, Jenkins is the easiest platform for someone who has no experience to come in and use effectively. We can get a junior engineer into Jenkins, give them access, and point them in the right direction with minimal hand-holding. The competing products I have used (TravisCI/GitLab/Azure) provide other options but can obfuscate the process due to the lack of straightforward simplicity. In other areas (capability, power, customization), Jenkins keeps up with the competition and, in some areas, like customization, exceeds others.
    Incentivized
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    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
    Open Source
    • Faster Time-to-Market: Jenkins automate the build, testing, and deployment process, enabling faster feedback and continuous improvement.
    • Improved Quality: Jenkins automatically run unit tests and integration tests, ensuring that code changes meet the necessary quality standards.
    • Cost Savings: Jenkins is an open-source tool that is free to use
    Incentivized
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    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
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