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AWS Data Exchange

AWS Data Exchange

Overview

What is AWS Data Exchange?

AWS Data Exchange is an integration for data service, from which subscribers can easily browse the AWS Data Exchange catalog to find relevant and up-to-date commercial data products covering a wide range of industries, including financial services, healthcare, life sciences,…

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Recent Reviews
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Pricing

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What is AWS Data Exchange?

AWS Data Exchange is an integration for data service, from which subscribers can easily browse the AWS Data Exchange catalog to find relevant and up-to-date commercial data products covering a wide range of industries, including financial services, healthcare, life sciences, geospatial, consumer,…

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  • No setup fee

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  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Product Details

What is AWS Data Exchange?

AWS Data Exchange Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Comparisons

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Reviews and Ratings

(8)

Attribute Ratings

Reviews

(1-2 of 2)
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Ike Bennion | TrustRadius Reviewer
Score 1 out of 10
Vetted Review
Verified User
We wanted to use AWS Data Exchange to list, sell and deliver our dataset in the open market. We have roughly 22 datasets that cover specific topical areas and industries. We update these sets on a monthly or quarterly basis depending on the data.
  • Allow you to make private transactions of data
  • Organize your datasets
  • Provide custom legal data services agreements
  • Poor transparency for sellers
  • Little verification of accounts requesting subscriptions
  • Confusing, buggy and misleading UX
  • Very poor development focus, roadmap and investment in the product
  • Bad experience for buyers of the data
  • Poor account service
  • If you have a small number of institutions you know well that you want to deliver data to securely, AWS could be a solution for you.
  • If you want to sell or provide visibility of your data, you could create a product page and then do your best to take the transaction off-exchange.
Data Source Connection (2)
35%
3.5
Connect to traditional data sources
70%
7.0
Connecto to Big Data and NoSQL
N/A
N/A
Data Transformations (2)
N/A
N/A
Simple transformations
N/A
N/A
Complex transformations
N/A
N/A
Data Modeling (5)
N/A
N/A
Data model creation
N/A
N/A
Metadata management
N/A
N/A
Business rules and workflow
N/A
N/A
Collaboration
N/A
N/A
Testing and debugging
N/A
N/A
Data Governance (2)
N/A
N/A
Integration with data quality tools
N/A
N/A
Integration with MDM tools
N/A
N/A
  • AWS Data Exchange required a lot of time to setup and was hard to QA
  • We have had a lot of traffic flow to ADX with no conversion.
  • We had bad transactions because of compromised accounts, but AWS doesn't provide sellers with enough information/verification to trust subscription request
  • Buggy user experience so there have been erroneous details about our listings
  • Confusing documentation that is often not detailed enough or erroneous
3
We have engineering, product and marketing who are involved with the AWS Data Exchange.
1
Basic skills but the administration of the system is time intensive.
  • Data delivery
  • Payment processing
  • Marketing and advertising
There have been a lot of problems with ADX. First, the entire system is incredibly clunky from beginning to end.First, by AWS's own admission they're missing a lot of "tablestakes functionality" like the ability to see who is coming to your pages, more flexibility to edit and update your listings, the ability to create a storefront or catalog that actually tries to sell your products. All-in-all you're flying completely blind with AWS. In our convos with other sellers we strongly believe very little organic traffic is flowing through the AWS exchange. For the headache, it's not worth the time or the effort. It's very difficult to market or sell your products.We've also had a number of simple UX bugs where they just don't accurately reflect the attributes of your product. For instance for an S3 bucket they had "+metered costs" displayed to one of our buyers in the price. This of course caused a lot of confusion. They also misrepresented the historical revisions that were available in our product sets because of another UX bug. It's difficult to know what other things in the UX are also broken and incongruent.We also did have a purchase, but the seller is completely at their whim at providing you fake emails, fake company names, fake use cases because AWS hasn't thought through simple workflows like "why even have subscription confirmation if I can fake literally everything about a subscription request." So as a result we're now in an endless, timewasting, unhelpful thread with AWS support trying to get payment. They're confused of what to do and we feel completely lost.Lastly, the AWS team has been abysmal in addressing our concerns. Conversations with them result in a laundry list of excuses of why simple functionalities are so hard (including just having accurate documentation). It was a very frustrating and unproductive call. Our objective of our call was to help us see that ADX is a well-resourced and well-visioned product. Ultimately they couldn't clearly articulate who they built the exchange for both on the seller side and the buyer side.Don't waste your time. This is at best a very foggy experiment. Look at other sellers, they have a lot of free pages to try to get attention, but then have smart tactics to divert transactions away from the ADX. Ultimately, smart move. Why give 8-10% of your cut to a product that is basically bare-bones infrastructure.
Ramindu Deshapriya | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use AWS Data Exchange as a straightforward solution to publish datasets from our healthcare solutions platform. This is a great way to get simulated datasets that we generate using machine learning methodologies out to potential clients, and to encourage the various partnerships we have with research divisions at universities that use datasets generated by our organization. Being able to point AWS Data Exchange at existing data sources such as AWS S3 and AWS Redshift has really helped us to simplify the process of delivering data to our clients and users.
  • Simplified data delivery
  • Ability to create any amount of data products
  • Ability to integrate payment plans with data products
  • Tracking data downloads and users
  • Integration with other AWS data services
  • Integration with more data sources
  • Ability to deliver data to clients without AWS accounts
  • Inclusion of direct data downloads in addition to asynchronous methods
AWS Data Exchange fits best for scenarios where you have datasets that you would like to sell and you want to deliver it to anyone who would like to purchase it. It really beats having to set up downloads via your own website or portal. However, it can get complicated to manage if you're trying to deliver a dataset a client has already paid for.
Data Source Connection (2)
75%
7.5
Connect to traditional data sources
60%
6.0
Connecto to Big Data and NoSQL
90%
9.0
Data Transformations
N/A
N/A
Data Modeling (5)
82%
8.2
Data model creation
90%
9.0
Metadata management
90%
9.0
Business rules and workflow
70%
7.0
Collaboration
90%
9.0
Testing and debugging
70%
7.0
Data Governance (1)
70%
7.0
Integration with data quality tools
70%
7.0
  • Reduced time to publish datasets for sale by more than 80%
  • Increased net profit from dataset sales by ~10%
  • Reduced data delivery time to clients by 15%
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