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  1. Home
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  3. Cloudera AI
Logo of Cloudera AI

Cloudera AI

byCloudera
in
4.4
Market Presence: Data Science and Machine Learning Platforms (Transitioning to AI Platforms For Data Science and Machine Learning), Cloud Database Management Systems

Overview

Product Information on Cloudera AI

Updated 13th October 2025

What is Cloudera AI?

Cloudera AI is a software designed to support enterprise machine learning and artificial intelligence workflows within a unified data platform. It offers tools for managing the entire lifecycle of AI and ML models, including data preparation, model training, deployment, and monitoring. The software facilitates collaboration among data scientists and engineers by providing access to scalable compute resources and integrating with various open-source frameworks. Cloudera AI addresses business challenges related to data silos and operationalizing AI by simplifying model governance and ensuring secure access to data. It also includes features for automating machine learning processes, enabling organizations to accelerate development and deployment of AI solutions while managing compliance and security requirements throughout the workflow.

Cloudera AI Pricing

Cloudera AI software follows a subscription-based pricing model where charges are typically based on the required features, usage levels, and deployment size. Pricing tiers may vary according to the volume of data, number of users, and specific modules included as part of the software package. Enterprise contracts and cloud service usage can influence overall cost structure, and custom pricing arrangements are also available for larger deployments.

Overall experience with Cloudera AI

Data Scientist
30B + USD, Healthcare and Biotech
FAVORABLE

“CML quick review”

4.0
Mar 26, 2024
The CML platform certainly provides a lot of flexibility to developers in selecting IDEs and session profiles for model development. However, CML needs to improve on it's Model Registry, error messages and application deployment area.
Data Scientist
50M - 250M USD, Banking
CRITICAL

“Good sandbox environment for starter Data Science.”

3.0
Jun 27, 2021
CDSW is good when we are using SPARK by authorize through Keberos. For global variable or passing parameter through pipeline still not good enough

About Company

Company Description

Updated 13th January 2025

Cloudera focuses on enabling transformation of complex data into clear and actionable insights. It provides an enterprise data cloud for data management, catering to multiple locations from the Edge to AI. Leveraging the continuous development aspects of the open source community, Cloudera caters to the digital transformation needs of large-scale enterprises around the world.

Company Details

Updated 26th February 2025
Company type
Private
Year Founded
2008
Head office location
Santa Clara, United States
Number of employees
1001 - 5000
Website
https://www.cloudera.com

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Key Insights

A Snapshot of What Matters - Based on Validated User Reviews

Reviewer Insights for: Cloudera AI
Deciding Factors: Cloudera AI Vs. Market Average
Performance of Cloudera AI Across Market Features

Cloudera AI Likes & Dislikes

Like

1) Collaborative development and quick integration with Github 2) Nice and intuitive application deployment (including Streamlit, Flask and Gradio) 3) AMPs are certainly helpful to get started quickly.

Like

Isolation Environment for each Data Scientists on Image Docker

Like

Ease of use is great, but really the most valuable has been the speed with which I can go from start to measurable impact.

Dislike

1) Application deployment should have feature to auto-notify when application is down or unavailable 2) Include more GenAI AMPs to dive into CML capabilities 3) Slow feature releases by Cloudera vendor

Dislike

Hard to passing parameter between scripts.

Dislike

didn't see training options in Cloudera

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Peer Discussions

Cloudera AI Reviews and Ratings

4.4

(66 Ratings)

Rating Distribution

5 Star
48%
4 Star
44%
3 Star
8%
2 Star
0%
1 Star
0%
Why ratings and reviews count differ?

Customer Experience

Evaluation & Contracting

4.4

Integration & Deployment

4.2

Service & Support

4.4

Product Capabilities

4.4

Filter Reviews
Sort By:
Most helpful
Last 12 Months
Star Rating
Reviewer Type
Reviewer's Company Size
Reviewer's Industry
Reviewer's Region
Reviewer's Job Function
  • Data Scientist
    10B+ USD
    Healthcare and Biotech
    Review Source

    CML quick review

    4.0
    Mar 26, 2024
    The CML platform certainly provides a lot of flexibility to developers in selecting IDEs and session profiles for model development. However, CML needs to improve on it's Model Registry, error messages and application deployment area.
  • Data Analyst
    50M-1B USD
    Energy and Utilities
    Review Source

    The path to no-code goes through Cloudera

    5.0
    Mar 28, 2024
    Overall experience is Exceptional. The rep. and others I've interacted with have raised the bar on professionalism, technical ability, communication - both within their organization and helping me navigate some within mine.
  • Lead Data Engineer
    50M-1B USD
    IT Services
    Review Source

    Cloudera Machine Learning Review

    4.0
    Apr 2, 2024
    The product is very useful for data scientists, however there are some operational and integration overheads.
  • MANAGEMENT CONSULTANT
    10B+ USD
    Miscellaneous
    Review Source

    Streamline data science process and enhance collaboration

    5.0
    Aug 19, 2023
    Cloudera platform has empowered our organization with robust capabilities for data science and machine learning. It provides a collaborative environment for data scientists to develop and manage mill models effectively. It has allowed us to extract meaningful insights from data and develop predictive models that drive informed business decisions.
  • INSTRUCTIONAL DESIGNER
    <50M USD
    Healthcare and Biotech
    Review Source

    Empowering enterprise scale AI with unified collaboration, scalability and integration

    4.0
    May 30, 2023
    It offers a unified environment that simplifies collaboration between data scientist and IT teams. The scalability is impressive, I was able to process and analyze massive datasets without any performance bottlenecks, which greatly enhanced the ML capabilities. Whereas it is a little tricky to navigate, documentation and support lacked clear examples and explanation, it resources requirement are high.
...
Showing Result 1-5 of 66

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Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.

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