Cloudera DataFlow vs Starburst Enterprise comparison

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Cloudera Logo
1,875 views|947 comparisons
75% willing to recommend
Starburst Logo
909 views|828 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Cloudera DataFlow and Starburst Enterprise based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics.
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Featured Review
Prathamesh D Marathe
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The most effective features are data management and analytics.""The initial setup was not so difficult""DataFlow's performance is okay.""This solution is very scalable and robust."

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"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

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Cons
"It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning.""It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists.""Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages."

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"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

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Pricing and Cost Advice
  • "DataFlow isn't expensive, but its value for money isn't great."
  • More Cloudera DataFlow Pricing and Cost Advice →

  • "I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."
  • More Starburst Enterprise Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:The most effective features are data management and analytics.
    Top Answer:We use Cloudera DataFlow for stream analytics.
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    Ranking
    13th
    out of 39 in Streaming Analytics
    Views
    1,875
    Comparisons
    947
    Reviews
    4
    Average Words per Review
    294
    Rating
    7.3
    14th
    out of 39 in Streaming Analytics
    Views
    909
    Comparisons
    828
    Reviews
    1
    Average Words per Review
    747
    Rating
    8.0
    Comparisons
    Also Known As
    CDF, Hortonworks DataFlow, HDF
    Learn More
    Overview

    Cloudera DataFlow (CDF) is a comprehensive edge-to-cloud real-time streaming data platform that gathers, curates, and analyzes data to provide customers with useful insight for immediately actionable intelligence. It resolves issues with real-time stream processing, streaming analytics, data provenance, and data ingestion from IoT devices and other sources that are associated with data in motion. Cloudera DataFlow enables secure and controlled data intake, data transformation, and content routing because it is built entirely on open-source technologies. With regard to all of your strategic digital projects, Cloudera DataFlow enables you to provide a superior customer experience, increase operational effectiveness, and maintain a competitive edge.

    With Cloudera DataFlow, you can take the next step in modernizing your data streams by connecting your on-premises flow management, streams messaging, and stream processing and analytics capabilities to the public cloud.

    Cloudera DataFlow Advantage Features

    Cloudera DataFlow has many valuable key features. Some of the most useful ones include:

    • Edge and flow management: Edge agents and an edge management hub work together to provide the edge management capability. Edge agents can be managed, controlled, and watched over in order to gather information from edge hardware and push intelligence back to the edge. Thousands of edge devices can now be used to design, deploy, run, and monitor edge flow apps. Edge Flow Manager (EFM) is an agent management hub that enables the development, deployment, and monitoring of edge flows on thousands of MiNiFi agents using a graphical flow-based programming model.
    • Streams messaging: The CDF platform guarantees that all ingested data streams can be temporarily buffered so that other applications can use the data as needed. This makes it possible for a business to scale efficiently, as data streams from thousands of origination points start to grow to petabyte sizes. To achieve IoT-scale, streams messaging allows you to buffer large data streams using a publish-subscribe strategy.
    • Stream analytics and processing: The third tenet of the CDF platform is its capacity to analyze incoming data streams in real time and with minimal latency, providing actionable intelligence in the form of predictive and prescriptive insights. This stage is essential to completing the Data-in-Motion lifecycle for an enterprise because there is only a use in absorbing all real-time streams if something useful is done with them in the moment to benefit your company.
    • Shared Data Experience (SDX): The most crucial component that transforms CDF into a genuine platform is Cloudera Data Platform's SDX. It is a powerful data fabric that offers the broadest possible deployment flexibility and guarantees total security, governance, and control across infrastructures. You get a single experience for security (with Apache Ranger), governance (with Apache Atlas), and data lineage from edge to cloud because all the CDF components seamlessly connect with SDX.

    Cloudera DataFlow Advantage Benefits

    There are many benefits to implementing Cloudera DataFlow . Some of the biggest advantages the solution offers include:

    • Completely open source: Invest in your architecture with confidence, knowing that there will be no vendor lock-in.
    • More than 300 pre-built processors: This is the only product that provides edge-to-cloud connection this comprehensive as well as a no-code user experience
    • Integrated data provenance: The market's only platform that offers out-of-the-box, end-to-end data lineage tracking and provenance across MiNiFi, NiFi, Kafka, Flink, and more.
    • Multiple stream processing engines to choose from: Supports Spark structured streaming, Kafka Streams, and Apache Flink for real-time insights and predictive analytics.
    • Hundred of Kafka consumers: Cloudera has hundreds of satisfied customers who receive exceptional support for their complex Kafka implementations.
    • Use cases for edge IoT: IoT data from thousands of endpoints may be easily collected, processed, and managed from the edge to the cloud with a multi-cloud/hybrid cloud strategy.
    • Hybrid/multi-cloud approach: Choose a flexible deployment option for your streaming architecture that spans across edge, on-premises, and various cloud environments with ease thanks to the power of CDP.

    Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems. 

    By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

    Sample Customers
    Clearsense
    Information Not Available
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company19%
    Financial Services Firm15%
    University8%
    Government7%
    VISITORS READING REVIEWS
    Financial Services Firm37%
    Computer Software Company11%
    Manufacturing Company5%
    Healthcare Company5%
    Company Size
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise10%
    Large Enterprise74%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise9%
    Large Enterprise76%
    Buyer's Guide
    Streaming Analytics
    May 2024
    Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics. Updated: May 2024.
    772,679 professionals have used our research since 2012.

    Cloudera DataFlow is ranked 13th in Streaming Analytics with 4 reviews while Starburst Enterprise is ranked 14th in Streaming Analytics with 1 review. Cloudera DataFlow is rated 7.2, while Starburst Enterprise is rated 8.0. The top reviewer of Cloudera DataFlow writes "Has good data management and analytics features". On the other hand, the top reviewer of Starburst Enterprise writes "Handles complex data and improves performance ". Cloudera DataFlow is most compared with Databricks, Confluent, Amazon MSK, Hortonworks Data Platform and Informatica Data Engineering Streaming, whereas Starburst Enterprise is most compared with Dremio, Starburst Galaxy, Alteryx, Databricks and Apache Spark Streaming.

    See our list of best Streaming Analytics vendors.

    We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.