The Cloudera Enterprise Data Hub powered by SDX is a multifunction analytics solution that supports a range of operational and analytic use cases for enterprises.
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Dataiku
Score 8.5 out of 10
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The Dataiku platform unifies data work from analytics to Generative AI. It supports enterprise analytics with visual, cloud-based tooling for data preparation, visualization, and workflow automation.
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Pricing
Cloudera Enterprise Data Hub
Dataiku
Editions & Modules
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Offerings
Pricing Offerings
Cloudera Enterprise Data Hub
Dataiku
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Cloudera Enterprise Data Hub
Dataiku
Features
Cloudera Enterprise Data Hub
Dataiku
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Cloudera Enterprise Data Hub
-
Ratings
Dataiku
8.6
5 Ratings
3% above category average
Connect to Multiple Data Sources
00 Ratings
8.05 Ratings
Extend Existing Data Sources
00 Ratings
10.04 Ratings
Automatic Data Format Detection
00 Ratings
10.05 Ratings
MDM Integration
00 Ratings
6.52 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Cloudera Enterprise Data Hub
-
Ratings
Dataiku
10.0
5 Ratings
17% above category average
Visualization
00 Ratings
10.05 Ratings
Interactive Data Analysis
00 Ratings
10.05 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Cloudera Enterprise Data Hub
-
Ratings
Dataiku
9.5
5 Ratings
15% above category average
Interactive Data Cleaning and Enrichment
00 Ratings
9.05 Ratings
Data Transformations
00 Ratings
9.05 Ratings
Data Encryption
00 Ratings
10.04 Ratings
Built-in Processors
00 Ratings
10.04 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Cloudera Enterprise Data Hub
-
Ratings
Dataiku
8.5
5 Ratings
1% above category average
Multiple Model Development Languages and Tools
00 Ratings
8.05 Ratings
Automated Machine Learning
00 Ratings
8.05 Ratings
Single platform for multiple model development
00 Ratings
8.05 Ratings
Self-Service Model Delivery
00 Ratings
10.04 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Cloudera excels at seamless migrations and upgrades.
Cloudera supports self-healing and data center replacement of failed cloud instances while maintaining the state.
Cloudera is essential to increase or decrease capacity through the user interface or API.
Cloudera is great at simplifying big data analytics by providing the technology and tools needed to gain insights from IoT and connected devices to help monitor and condition our assets.
Cloudera's cybersecurity platform option offers stronger anomaly detection, visibility, and prevention, as well as faster behavioral analysis.
Cloudera is beneficial for enabling and utilizing the platform's machine learning and ad-hoc queries while securely storing, retrieving, and analyzing any volume of data at scale.
Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.
The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.
Likely to renew the use in case the requirements for Cloudera remain valid. The rapid change in customer requirements and solutions that must be validated, integrated or tested changes. As the maturity of the solution increases, the requirements to renew use decrease. From a solution feature perspective by itself would probably grade 10.
The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level
The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
Cloudera is compatible with Windows operating systems, and Mac allows cloud-based deployment, it is also very useful to configure data encryption, guarantee protocols, and security policies. It also provides integrated auditing and monitoring capabilities, as well as a control comprehensive data repository for the enterprise, and ensures vendor compatibility through its open-source architecture.
Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
Cloudera products are the most widely. It is more business friendly as data is more secure. The sensitive data that you operate on is local to you and your project rather than processing this data on Cloud.
Cloudera is definitely faster as wait time is reduced if on Cloud.
A lot range of products are covered. So it is definitely good for businesses and had good returns on investments.