Software Alternatives, Accelerators & Startups

SAS Model Manager VS Tibco Data Science

Compare SAS Model Manager VS Tibco Data Science and see what are their differences

SAS Model Manager logo SAS Model Manager

SAS Model Manager is a proven, reliable solution for the Analysis Services platform that enables you to integrate multiple environments, tools, and applications using open REST APIs.

Tibco Data Science logo Tibco Data Science

Data science is a team sport. Data scientists, citizen data scientists, business users, and developers need flexible and extensible tools that promote collaboration, automation, and...
  • SAS Model Manager Landing page
    Landing page //
    2023-10-05
  • Tibco Data Science Landing page
    Landing page //
    2022-10-04

SAS Model Manager features and specs

  • Comprehensive Model Management
    SAS Model Manager provides a robust environment for managing the entire model lifecycle, including building, deploying, monitoring, and retraining models. It helps ensure models remain accurate and relevant over time.
  • Seamless Integration
    The tool integrates well with the broader SAS ecosystem and can handle models developed using various languages and tools like Python and R, allowing for flexibility in model development.
  • Advanced Monitoring and Reporting
    SAS Model Manager offers advanced capabilities for monitoring model performance and creating detailed reports, which can help in ensuring transparency and compliance with regulations.
  • Scalability
    Designed to handle enterprise-level data and models, the software can scale to meet the demands of large organizations, allowing for the management of numerous models across various domains.
  • Automated Workflow
    The software supports automation of repetitive tasks, facilitating streamlined workflows and reducing manual intervention, which can lead to increased efficiency.

Possible disadvantages of SAS Model Manager

  • Cost
    The pricing of SAS Model Manager can be high, especially for smaller organizations or startups, posing a financial barrier to access for some users.
  • Complexity
    Given its comprehensive features, the platform can be complex to set up and use, requiring users to have a certain level of expertise or training to fully leverage its capabilities.
  • Dependency on SAS Environment
    While integration with the SAS ecosystem is a strength, it also means reliance on SAS-specific environments and systems, which may not be ideal for organizations using a diverse array of tools.
  • Limited Open-Source Support
    Compared to open-source alternatives, SAS Model Manager might offer less flexibility in terms of customization and adapting to unique, non-standard use cases.
  • User Interface
    Some users might find the user interface less intuitive compared to more modern or specialized model management tools, possibly impacting user experience.

Tibco Data Science features and specs

  • Scalability
    Tibco Data Science is designed to handle large amounts of data and scale as your needs grow, making it suitable for enterprise-level applications.
  • Integration Capabilities
    The platform integrates seamlessly with other TIBCO products and a wide array of third-party applications, enhancing its utility within diverse business environments.
  • User-Friendly Interface
    It offers a drag-and-drop interface which simplifies data processing and model building, making it accessible even for users with limited coding knowledge.
  • Collaboration Features
    Tibco Data Science allows teams to work together efficiently on projects, with features that support collaboration, version control, and sharing of data models.
  • Real-time Analytics
    The platform supports real-time analytics, useful for applications requiring immediate insights and decision-making.
  • Comprehensive Toolset
    It provides a wide range of tools for data manipulation, machine learning, and statistical analyses, offering a one-stop solution for data scientists.

Possible disadvantages of Tibco Data Science

  • Cost
    The platform can be expensive, particularly for smaller businesses or startups, making it less accessible for organizations with limited budgets.
  • Complexity
    Despite its user-friendly interface, the platform has a steep learning curve due to its extensive features and capabilities, which might overwhelm new users.
  • Resource Intensive
    Tibco Data Science can be resource-intensive, requiring powerful hardware and significant computational resources, which may pose challenges for some organizations.
  • Limited Flexibility
    While it integrates well with other TIBCO products, users sometimes find it less flexible when integrating with non-TIBCO technologies or legacy systems.
  • License Restrictions
    The platform has specific license restrictions and conditions that can limit flexibility in deployment and scaling, potentially complicating its use under certain circumstances.
  • Customer Support
    Users have reported that customer support can be slow at times and may not always provide satisfactory solutions to complex issues.

SAS Model Manager videos

Open-Source Model Management with SAS Model Manager

Tibco Data Science videos

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Category Popularity

0-100% (relative to SAS Model Manager and Tibco Data Science)
Business & Commerce
34 34%
66% 66
Technical Computing
0 0%
100% 100
Data Dashboard
51 51%
49% 49
Personalization
100 100%
0% 0

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Reviews

These are some of the external sources and on-site user reviews we've used to compare SAS Model Manager and Tibco Data Science

SAS Model Manager Reviews

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Tibco Data Science Reviews

Top 7 Predictive Analytics Tools
TIBCO Data Science/Statistica puts the emphasis on usability, with a lot of collaboration and workflow features built into the tool to make business intelligence possible across an organization. This makes it a good choice for a company if they expect lesser-trained staff will use the tool. It also integrates with a wide range of other analytics tools, making it easy to...
15 data science tools to consider using in 2021
The development of SAS started in 1966 at North Carolina State University; use of the technology began to grow in the early 1970s, and SAS Institute was founded in 1976 as an independent company. The software was initially built for use by statisticians -- SAS was short for Statistical Analysis System. But, over time, it was expanded to include a broad set of functionality...
The 16 Best Data Science and Machine Learning Platforms for 2021
Description: TIBCO offers an expansive product portfolio for modern BI, descriptive and predictive analytics, and streaming analytics and data science. TIBCO Data Science lets users do data preparation, model building, deployment and monitoring. It also features AutoML, drag-and-drop workflows, and embedded Jupyter Notebooks for sharing reusable modules. Users can run...

What are some alternatives?

When comparing SAS Model Manager and Tibco Data Science, you can also consider the following products

Xyonix - Xyonix is an AI Consulting and Data Science Solution that brings AI, Machine Learning, and Deep Learning to businesses by providing Software Engineering and Advisory services.

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

MLOps - MLOps is a software platform that enables companies to manage AI production.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

Robust Intelligence - Robust intelligence is stress and failure testing solution for AI models.

Alteryx - Alteryx provides an indispensable and easy-to-use analytics platform for enterprise companies making critical decisions that drive their business strategy and growth.