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    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

    IBM SPSS Modeler

    Score9.6 out of 10
    N/AIBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.

    $499

    per month

    Pricing
    EclipseIBM SPSS Modeler
    Editions & Modules
    No answers on this topic
    IBM SPSS Modeler Personal
    4,670
    per year
    IBM SPSS Modeler Professional
    7,000
    per year
    IBM SPSS Modeler Premium
    11,600
    per year
    IBM SPSS Modeler Gold
    contact IBM
    per year
    Offerings
    Pricing Offerings
    EclipseIBM SPSS Modeler
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details—IBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.
    More Pricing Information
    Community Pulse
    EclipseIBM SPSS Modeler
    Considered Both Products
    Open Source
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    94%
    Would buy again
    29 Answers
    100%
    Would buy again
    5 Answers
    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
    100%
    Happy with the feature set
    5 Answers
    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
    Features
    EclipseIBM SPSS Modeler
    Platform Connectivity
    Comparison of Platform Connectivity features of Eclipse and IBM SPSS Modeler
    Feature
    Eclipse
    -
    Ratings
    IBM SPSS Modeler
    8.9
    2 Ratings
    6% above category average
    Connect to Multiple Data Sources00 Ratings8.82 Ratings
    Extend Existing Data Sources00 Ratings8.82 Ratings
    Automatic Data Format Detection00 Ratings9.01 Ratings
    MDM Integration00 Ratings9.01 Ratings
    Data Exploration
    Comparison of Data Exploration features of Eclipse and IBM SPSS Modeler
    Feature
    Eclipse
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    7% above category average
    Visualization00 Ratings9.01 Ratings
    Interactive Data Analysis00 Ratings9.01 Ratings
    Data Preparation
    Comparison of Data Preparation features of Eclipse and IBM SPSS Modeler
    Feature
    Eclipse
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    10% above category average
    Interactive Data Cleaning and Enrichment00 Ratings9.01 Ratings
    Data Transformations00 Ratings9.01 Ratings
    Data Encryption00 Ratings9.01 Ratings
    Built-in Processors00 Ratings9.01 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Eclipse and IBM SPSS Modeler
    Feature
    Eclipse
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    Multiple Model Development Languages and Tools00 Ratings9.01 Ratings
    Automated Machine Learning00 Ratings9.01 Ratings
    Single platform for multiple model development00 Ratings9.01 Ratings
    Self-Service Model Delivery00 Ratings9.01 Ratings
    Model Deployment
    Comparison of Model Deployment features of Eclipse and IBM SPSS Modeler
    Feature
    Eclipse
    -
    Ratings
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    Flexible Model Publishing Options00 Ratings9.01 Ratings
    Security, Governance, and Cost Controls00 Ratings9.01 Ratings
    Best Alternatives
    EclipseIBM SPSS Modeler
    Small Businesses
    No answers on this topic
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    No answers on this topic
    Anaconda
    Score8.8 out of 10
    Enterprises
    No answers on this topic
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    EclipseIBM SPSS Modeler
    Likelihood to Recommend
    9.9
    (74 ratings)
    9.7
    (8 ratings)
    Likelihood to Renew
    9.0
    (1 ratings)
    -
    (0 ratings)
    Usability
    8.0
    (3 ratings)
    8.9
    (2 ratings)
    Support Rating
    6.8
    (19 ratings)
    10.0
    (1 ratings)
    User Testimonials
    EclipseIBM SPSS Modeler
    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
    IBM
    Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
    Incentivized
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    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
    IBM
    • Combine text and data
    • Provide facilities for all phases of the data mining process.
    • Use a node and stream paradigm to easily and quickly create models.
    Incentivized
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    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
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    IBM
    • Has very old style graphs, with lots of limitations.
    • Some advanced statistical functions cannot be done through the menu.
    • The data connectivity is not that extensive.
    • It's an expensive tool.
    Incentivized
    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
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    IBM
    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
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    IBM
    The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
    Incentivized
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    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
    IBM
    The online support board is helpful and the free add ons are incredibly appreciated.
    Incentivized
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    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
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    IBM
    When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
    Incentivized
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    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
    IBM
    • Positive - Ease of decision making and reduction in product life cycle time.
    • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
    • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
    Incentivized
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    ScreenShots

    IBM SPSS Modeler Screenshots

    Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.