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Azure Anomaly Detector vs. Google Cloud Dataflow

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Azure Anomaly Detector

4 Reviews and Ratings

Google Cloud Dataflow

37 Reviews and Ratings

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure Anomaly Detector

    Score8.9 out of 10
    		N/AAnomaly Detector on Microsoft's Azure is an AI service that helps foresee problems. Users can embed time-series anomaly detection capabilities into apps to help users identify problems quickly. Anomaly Detector ingests time-series data of all types and selects the best anomaly detection algorithm for the data to support high accuracy. Detect spikes, dips, deviations from cyclic patterns, and trend changes through both univariate and multivariate APIs. The service can be customized to detect any…N/A

    Google Cloud Dataflow

    Score9.1 out of 10
    		N/AGoogle offers Cloud Dataflow, a managed streaming analytics platform for real-time data insights, fraud detection, and other purposes.N/A
    Pricing
    Azure Anomaly DetectorGoogle Cloud Dataflow
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Azure Anomaly DetectorGoogle Cloud Dataflow
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Features
    Azure Anomaly DetectorGoogle Cloud Dataflow
    Streaming Analytics
    Comparison of Streaming Analytics features of Azure Anomaly Detector and Google Cloud Dataflow
    Feature
    Azure Anomaly Detector
    -
    Ratings
    Google Cloud Dataflow
    7.3
    2 Ratings
    7% below category average
    Real-Time Data Analysis00 Ratings8.02 Ratings
    Visualization Dashboards00 Ratings5.01 Ratings
    Data Ingestion from Multiple Data Sources00 Ratings9.02 Ratings
    Low Latency00 Ratings9.02 Ratings
    Integrated Development Tools00 Ratings6.01 Ratings
    Data wrangling and preparation00 Ratings7.01 Ratings
    Linear Scale-Out00 Ratings8.02 Ratings
    Machine Learning Automation00 Ratings6.02 Ratings
    Data Enrichment00 Ratings8.02 Ratings
    Best Alternatives
    Azure Anomaly DetectorGoogle Cloud Dataflow
    Small Businesses
    Amazon Kinesis
    Score9.9 out of 10
    Amazon Kinesis
    Score9.9 out of 10
    Medium-sized Companies
    No answers on this topic
    No answers on this topic
    Enterprises
    Spotfire Streaming
    Score5 out of 10
    Spotfire Streaming
    Score5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Azure Anomaly DetectorGoogle Cloud Dataflow
    Likelihood to Recommend
    -
    (0 ratings)
    9.0
    (2 ratings)
    Usability
    -
    (0 ratings)
    8.0
    (1 ratings)
    User Testimonials
    Azure Anomaly DetectorGoogle Cloud Dataflow
    Likelihood to Recommend
    Microsoft
    No answers on this topic
    Google
    It is best in cases where you have batch as well as streaming data. Also in some cases where you have batch data right now and in future you will get streaming data. In those cases Dataflow is very good. Also in cases where most of your infra is on GCP. It might not be good when you already are on AWS or Azure. And also you want in-depth control over security and management. Then you can directly use Apache beam over Dataflow.
    Incentivized
    Verified User
    Read full review
    Pros
    Microsoft
    No answers on this topic
    Google
    • Streaming, Real time work load
    • Batch processing
    • Auto scaling
    • flexible pricing
    Sathish Palanivel(He/Him)
    Cloud Architect
    Read full review
    Cons
    Microsoft
    No answers on this topic
    Google
    • More templates for Bigquery and App Engine. There is only limited options for templates so the things we use can limit.
    • I would like native connectors for Excel (XLSX) to reduce the need for custom wrappers in financial pipelines.
    • Debugging Google Cloud Dataflow using only logs in Cloud Logging can be overwhelming sometimes, and it’s not always obvious which specific element in the flow caused a failure. IT uses a lot of time.
    Incentivized
    Verified User
    Read full review
    Usability
    Microsoft
    No answers on this topic
    Google
    It really saved a lot of time and it's flexibility really can give you infra which is future-proof for most of the use cases may it be streaming or batch data. And with this you can avoid use of resource-heavy big data offerings.
    Incentivized
    Verified User
    Read full review
    Alternatives Considered
    Microsoft
    No answers on this topic
    Google
    Google Cloud Dataproc Cloud Datafusion
    Sathish Palanivel(He/Him)
    Cloud Architect
    Read full review
    Return on Investment
    Microsoft
    No answers on this topic
    Google
    • cost saving from managing our own data center for ETL servers
    • consumption based pricing
    • with auto scaling feature, we were able to expand components to support work load
    Sathish Palanivel(He/Him)
    Cloud Architect
    Read full review
    ScreenShots