Cloudera DataFlowCloudera
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dataFactorydFakto
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Related Products
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About
Cloudera DataFlow for the Public Cloud (CDF-PC) is a cloud-native universal data distribution service powered by Apache NiFi that lets developers connect to any data source anywhere with any structure, process it, and deliver to any destination. CDF-PC offers a flow-based low-code development paradigm that aligns best with how developers design, develop, and test data distribution pipelines. With over 400+ connectors and processors across the ecosystem of hybrid cloud services—including data lakes, lakehouses, cloud warehouses, and on-premises sources—CDF-PC provides indiscriminate data distribution. These data distribution flows can then be version-controlled into a catalog where operators can self-serve deployments to different runtimes.
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About
Cut out all the manual processes, sources of errors, and wasted time. Don’t re-engineer your data warehouse every time a business change occurs. Apply automatic quality checks inter and intra-sources, and take action quickly when needed. That’s crucial for hundreds of data consumers. Trust really your data now. Build your “gold record” referential so the business teams have always the freshest data possible. One single version of the truth, available anywhere, anytime. Build an intermediate model that structures, stores, and historicizes your data independently of their uses. Answer fast to changing sources and business requests. From raw data to any system, connect all your sources easily as for the first one (datalake, operational systems, excels, relational database, legacy tools, etc. Store, historicize, and improve data quality to facilitate data warehouse automation. Data is structured, enriched, and documented to be available in datasets (information marts).
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
SMBs and enterprises looking for a powerful Event Stream Processing solution
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Audience
Organizations in need of a tool to turn raw data from multiple sources into qualitative information for effective decision making
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Support
Phone Support
Supported
24/7 Live Support
Supported
Online
Supported
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Support
Phone Support
Supported
24/7 Live Support
Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Supported
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Company InformationCloudera
Founded: 2008
United States
www.cloudera.com/products/cdf.html
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Company InformationdFakto
Founded: 2000
Belgium
www.dfakto.com/datafaktory-data-warehouse-automation/
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Categories |
Categories |
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Streaming Analytics Features
Data Enrichment
Supported
Data Wrangling / Data Prep
Supported
Multiple Data Source Support
Supported
Process Automation
Supported
Real-time Analysis / Reporting
Supported
Visualization Dashboards
Supported
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Integrations
Cloudera
Supported
Cloudera Data Platform
Supported
Google Sheets
Not Supported
Litmus Edge
Supported
Microsoft Excel
Not Supported
Microsoft Power BI
Not Supported
Qlik Data Integration
Not Supported
Tableau
Not Supported
Talend Data Preparation
Supported
Ternary
Supported
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Integrations
Cloudera
Not Supported
Cloudera Data Platform
Not Supported
Google Sheets
Supported
Litmus Edge
Not Supported
Microsoft Excel
Supported
Microsoft Power BI
Supported
Qlik Data Integration
Supported
Tableau
Supported
Talend Data Preparation
Not Supported
Ternary
Not Supported
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