Alteryx Designer Cloud vs. dataTap

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Alteryx Designer Cloud
Score 9.5 out of 10
N/A
Trifacta is a "data wrangling" (or data preparation) platform particularly of use with Hadoop, developed by the company Trifacta headquartered in San Francisco, California. Alteryx announced their acquisition of Trifacta in January of 2022.
$100
per month per user
dataTap
Score 0.0 out of 10
N/A
dataTap is a user friendly visual data management platform from Zensors. The dataTap Python library is the primary interface for using dataTap's data management tools. Users can create datasets, stream annotations, and analyze model performance all with one library. Zensors states with dataTap, users can: - Begin training instantly - Work with all major ML frameworks…N/A
Pricing
Alteryx Designer ClouddataTap
Editions & Modules
Starter
$100
per month per user
Professional
$500
per month per user
Enterprise
Custom
No answers on this topic
Offerings
Pricing Offerings
Alteryx Designer ClouddataTap
Free Trial
YesYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional DetailsStarter & Professional plans include a charge of + $0.60 / vCPU hour. 20% discount for annual pricing.
More Pricing Information
Best Alternatives
Alteryx Designer ClouddataTap
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
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Score 7.8 out of 10
Medium-sized Companies
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Score 8.1 out of 10
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Score 8.1 out of 10
Enterprises
IBM InfoSphere Information Server
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Score 8.1 out of 10
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All AlternativesView all alternativesView all alternatives
User Ratings
Alteryx Designer ClouddataTap
Likelihood to Recommend
8.2
(3 ratings)
-
(0 ratings)
User Testimonials
Alteryx Designer ClouddataTap
Likelihood to Recommend
Alteryx
For doing ETL and data transformations where your data is already in a cloud environment Alteryx Designer Cloud is ideal. It allows for the continued democratisation of data and analytics to permeate more extensively throughout a business, particularly those that are already in the cloud or have cloud services in place and are comfortable with procurement and consumption of these systems over and above desktop software. The ETL processing for data validation and wrangling uses machine learning to enable highly efficient data manipulation which saves lots of time and this is a distinct advantage over the desktop software. The expansion and integration of other Alteryx cloud services such as ML, Metrics Store and App builder will only strengthen this position
Read full review
Zensors Inc.
No answers on this topic
Pros
Alteryx
  • Gives automatic options for code.
  • Allows for notes on code.
  • Duplicates work and allows for repurposing work.
Read full review
Zensors Inc.
No answers on this topic
Cons
Alteryx
  • Hadoop source data tables are presented in a flat searchable list but I would rather see them in the native hierarchy.
  • Web interface can be flaky. We often need to refresh the page.
Read full review
Zensors Inc.
No answers on this topic
Alternatives Considered
Alteryx
Our IT group presented Trifacta to me. They picked it out and among the crowd for me. This was way beyond ETL tools, SQL, or any programming language. It's just much faster and because it's sitting on Hadoop you bypass some of the slowdowns typically faced with RDBMS.
Read full review
Zensors Inc.
No answers on this topic
Return on Investment
Alteryx
  • Increased productvity by 5x
  • Reduced costs of running and patching desktop and server based software entirely
Read full review
Zensors Inc.
No answers on this topic
ScreenShots

dataTap Screenshots

Screenshot of Install the client library.

`pip install datatap`

Register at [app.datatap.dev](https://app.datatap.dev/). Then, go to `Settings > Api Keys` to find your personal API key.

`export DATATAP_API_KEY="XXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXX"`

To begin with, select a dataset from the dataTap repositoryScreenshot of Copy the starter code based on your library preferenceScreenshot of Paste the starter code and start training.

from datatap import Api

api = Api()
coco = api.get_default_database().get_repository("_/coco")
dataset = coco.get_dataset("latest")
print("COCO: ", dataset)