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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    AWS Data Pipeline

    Score6 out of 10
    N/AAWS Data Pipeline is a web service used to process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, users can regularly access data where it’s stored, transform and process it at scale, and transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. AWS Data Pipeline is designed to help create complex data processing workloads that are fault tolerant,…N/A

    Mage AI

    Score8.6 out of 10
    N/AMage AI is a cloud-native Data Pipeline orchestration platform designed to facilitate the development, deployment, and management of data-intensive applications. The system provides a managed environment for building modular data workflows that integrate with existing cloud infrastructure and AI developer toolchains.

    $0

    per user

    Pricing
    AWS Data PipelineMage AI
    Editions & Modules
    No answers on this topic
    Hobby
    $0
    per user
    Pro
    $2,000
    per month per user
    Offerings
    Pricing Offerings
    AWS Data PipelineMage AI
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details—Contact vendor for pricing information.
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    Best Alternatives
    AWS Data PipelineMage AI
    Small Businesses
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    Medium-sized Companies
    Apache Spark
    Score8.8 out of 10
    No answers on this topic
    Enterprises
    Apache Spark
    Score8.8 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    AWS Data PipelineMage AI
    Likelihood to Recommend
    10.0
    (1 ratings)
    8.5
    (2 ratings)
    User Testimonials
    AWS Data PipelineMage AI
    Likelihood to Recommend
    Amazon AWS
    AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR.
    Incentivized
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    Mage
    Mage is well-suited for probability score for uptake of every product is calculated for customers using ML/ Regression models, choosing customers for a product/ Top products for a customer, based on the requirement and Identifying popular product combinations using association rules from Market Basket Analysis (or affinity Analysis)\Bundle these products as combos.
    Incentivized
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    Pros
    Amazon AWS
    • Helps you easily create complex data processing workloads
    • Fault tolerant
    • Highly available
    Incentivized
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    Mage
    • Ranking algorithms.
    • Cloud-based tool.
    • Increase user engagement.
    Incentivized
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    Cons
    Amazon AWS
    • Pipeline Stuck in Pending Status
    • Pipeline Component Stuck in Waiting for Runner Status
    • EMR Cluster Fails With Error
    Incentivized
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    Mage
    • Acquisition Contribution.
    • Business Intelligence Reporting.
    • Data Destinations.
    Incentivized
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    Alternatives Considered
    Amazon AWS
    AWS data pipelines are easy to use over data factory for data engineers
    Incentivized
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    Mage
    Mage was the easiest in terms of ease of implementation due to its no-code functionality. However, Mage doesn't have a whole ecosystem like AWS and slightly falls behind there.
    Incentivized
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    Return on Investment
    Amazon AWS
    • Easy to use
    • Data engineers are able to create the data pipelines quickly and effectively
    • Scalable and Fault tolerant
    Incentivized
    Read full review
    Mage
    • Business Understanding.
    • Data Acquisition and Understanding.
    • Data Modeling and Evaluation.
    Incentivized
    Read full review
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