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NVIDIA RAPIDS vs. Shakudo Platform

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NVIDIA RAPIDS

4 Reviews and Ratings

Shakudo Platform

1 Reviews and Ratings

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    NVIDIA RAPIDS

    Score9.1 out of 10
    		N/ANVIDIA RAPIDS is an open source software library for data science and analytics performed across GPUs. Users can run data science workflows with high-speed GPU compute and parallelize data loading, data manipulation, and machine learning for 50X faster end-to-end data science pipelines.N/A

    Shakudo Platform

    Score6 out of 10
    		N/AThe Shakudo platform ensures compatibility across data tools to allow companies to build the best data infrastructure for their needs. It supports over 60 popular data tools, and enables users to create the optimal data stack for any custom needs, and helps users to create a more reliable and performant stack. And it helps users to: Build a stack that works precisely for the company without worrying about maintenance costs or stability Using a single UI, let teams use and gain…N/A
    Pricing
    NVIDIA RAPIDSShakudo Platform
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    NVIDIA RAPIDSShakudo Platform
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Features
    NVIDIA RAPIDSShakudo Platform
    Platform Connectivity
    Comparison of Platform Connectivity features of NVIDIA RAPIDS and Shakudo Platform
    Feature
    NVIDIA RAPIDS
    9.1
    2 Ratings
    8% above category average
    Shakudo Platform
    -
    Ratings
    Connect to Multiple Data Sources9.62 Ratings00 Ratings
    Extend Existing Data Sources8.82 Ratings00 Ratings
    Automatic Data Format Detection9.02 Ratings00 Ratings
    MDM Integration9.01 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of NVIDIA RAPIDS and Shakudo Platform
    Feature
    NVIDIA RAPIDS
    9.4
    2 Ratings
    11% above category average
    Shakudo Platform
    -
    Ratings
    Visualization9.42 Ratings00 Ratings
    Interactive Data Analysis9.42 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of NVIDIA RAPIDS and Shakudo Platform
    Feature
    NVIDIA RAPIDS
    8.9
    2 Ratings
    8% above category average
    Shakudo Platform
    -
    Ratings
    Interactive Data Cleaning and Enrichment7.82 Ratings00 Ratings
    Data Transformations9.42 Ratings00 Ratings
    Data Encryption9.01 Ratings00 Ratings
    Built-in Processors9.42 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of NVIDIA RAPIDS and Shakudo Platform
    Feature
    NVIDIA RAPIDS
    9.2
    2 Ratings
    8% above category average
    Shakudo Platform
    -
    Ratings
    Multiple Model Development Languages and Tools9.01 Ratings00 Ratings
    Automated Machine Learning9.42 Ratings00 Ratings
    Single platform for multiple model development9.42 Ratings00 Ratings
    Self-Service Model Delivery9.01 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of NVIDIA RAPIDS and Shakudo Platform
    Feature
    NVIDIA RAPIDS
    9.2
    2 Ratings
    7% above category average
    Shakudo Platform
    -
    Ratings
    Flexible Model Publishing Options9.42 Ratings00 Ratings
    Security, Governance, and Cost Controls9.01 Ratings00 Ratings
    Best Alternatives
    NVIDIA RAPIDSShakudo Platform
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    Anaconda
    Score8.8 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    NVIDIA RAPIDSShakudo Platform
    Likelihood to Recommend
    10.0
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    NVIDIA RAPIDSShakudo Platform
    Likelihood to Recommend
    NVIDIA
    NVIDIA RAPIDS drastically improves our productivity with near-interactive data science. And increases machine learning model accuracy by iterating on models faster and deploying them more frequently. It gives us the freedom to execute end-to-end data science and analytics pipelines.
    Incentivized
    Douglas Carter
    Technical Manager
    Read full review
    Shakudo
    No answers on this topic
    Pros
    NVIDIA
    • Visualization
    • Deep learning pipeline
    • State of the art libraries
    Incentivized
    Mauro Bennici
    CTO (Chief Technical Officer)
    Read full review
    Shakudo
    No answers on this topic
    Cons
    NVIDIA
    • Its not flexible and cost effective for all sizes of organizations.
    • I appreciate it has hassle-free integration.
    Incentivized
    Douglas Carter
    Technical Manager
    Read full review
    Shakudo
    No answers on this topic
    Alternatives Considered
    NVIDIA
    RAPIDS GPU accelerates machine learning to make the entire data science and analytics workflows run faster, also helps build databases and machine learning applications effectively. It also allows faster model deployment and iterations to increase machine learning model accuracy. The great value of money.
    Incentivized
    Douglas Carter
    Technical Manager
    Read full review
    Shakudo
    No answers on this topic
    Return on Investment
    NVIDIA
    • Efficient way to complete tasks
    • De-facto GPUs standard
    Incentivized
    Mauro Bennici
    CTO (Chief Technical Officer)
    Read full review
    Shakudo
    No answers on this topic
    ScreenShots

    Shakudo Platform Screenshots

    Screenshot of Shakudo Platform Dashboard UIScreenshot of Jobs use the same environment config as Sessions, so users can have the same dependencies and configurations available as they had during development. Jobs can be run on demand using Immediate jobs, or scheduled with a Cron expression using Scheduled Jobs. The integrated Job system can be used on its own, or it can be used to run code with tools like Airflow or Prefect.Screenshot of When deploying a project and publishing the results, Services help to deploy custom long-running programs like web servers to host results, or integrations can be used. From publishing processed data to S3 buckets, to hosting trained models on Nvidia Triton, to publishing dashboards in Apache Superset, it helps data scientists deploy their projects and their artifacts with minimal configuration or maintenance required