AWS Data Exchange vs. IBM DataStage

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS Data Exchange
Score 9.8 out of 10
N/A
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, media & entertainment, and more.N/A
IBM DataStage
Score 7.6 out of 10
N/A
IBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.N/A
Pricing
AWS Data ExchangeIBM DataStage
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
AWS Data ExchangeIBM DataStage
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
AWS Data ExchangeIBM DataStage
Features
AWS Data ExchangeIBM DataStage
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
AWS Data Exchange
8.0
Ratings
5% below category average
IBM DataStage
9.5
Ratings
12% above category average
Connect to traditional data sources7.00 Ratings10.00 Ratings
Connecto to Big Data and NoSQL9.00 Ratings9.00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
AWS Data Exchange
8.2
Ratings
3% above category average
IBM DataStage
6.3
Ratings
23% below category average
Data model creation9.00 Ratings5.00 Ratings
Metadata management9.00 Ratings5.00 Ratings
Business rules and workflow7.00 Ratings6.00 Ratings
Collaboration9.00 Ratings6.00 Ratings
Testing and debugging7.00 Ratings6.00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
AWS Data Exchange
7.0
Ratings
15% below category average
IBM DataStage
6.0
Ratings
30% below category average
Integration with data quality tools7.00 Ratings6.00 Ratings
Integration with MDM tools00 Ratings6.00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
AWS Data Exchange
-
Ratings
IBM DataStage
8.0
Ratings
2% below category average
Simple transformations00 Ratings8.00 Ratings
Complex transformations00 Ratings8.00 Ratings
Best Alternatives
AWS Data ExchangeIBM DataStage
Small Businesses
Skyvia
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Score 9.9 out of 10
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Score 9.9 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
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Score 8.0 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
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User Ratings
AWS Data ExchangeIBM DataStage
Likelihood to Recommend
1.0
(0 ratings)
8.0
(0 ratings)
Likelihood to Renew
1.0
(0 ratings)
-
(0 ratings)
Usability
-
(0 ratings)
8.0
(0 ratings)
Performance
-
(0 ratings)
9.0
(0 ratings)
Support Rating
-
(0 ratings)
9.6
(0 ratings)
User Testimonials
AWS Data ExchangeIBM DataStage
Likelihood to Recommend
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.
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Excellent Cloud data mapping tool and easy creating multiple project data analytics in real-time and the report distribution are excellent via this IBM product. Easy tool to provide data visualization and the integration is effective and helpful to migrating huge amounts of data across other platforms and different websites insights gathering.
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Pros
  • 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
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  • Very reliable in handling data extraction, data transformation and loading
  • Flexibility in connecting to different type of databases, relational or non-relational
  • Great features such as parallel processing, hash handling, etc.
  • You can also take advantage of its FTP functions, and scheduling features if you need to.
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Cons
  • Integration with more data sources
  • Ability to deliver data to clients without AWS accounts
  • Inclusion of direct data downloads in addition to asynchronous methods
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  • You must understand and know the algorithms, since the wrong use of them generates more time in processing.
  • Metadata. You need to develop with connectors, and taking all the Metadata from the menu, all the data that you complete manually, you can't track it.
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Likelihood to Renew
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.
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No answers on this topic
Usability
No answers on this topic
Because it is a flexible tool that can manage many flows and create a strong solution with a interesting use of variables. Easy to scale up as you can copy jobs arleady build and modify them. SQL queries allow to be fast in development and have the pushdown feature, but you loose a little of user friendly look. Metadata management is not strong as a visual feature, but can be determine by job codes.
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Performance
No answers on this topic
It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
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Support Rating
No answers on this topic
IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.
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Alternatives Considered
No answers on this topic
No, it wasn’t my decision to use such an ETL product. I’m just the administrator at this point. I’ve heard there are other products there that are even on cloud support. That is much easier to use, more agile, and user-friendly. That doesn’t have that barrier from user to administrator to the developer standpoint.
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Return on Investment
  • 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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  • Not directly related to ROI or cost figures. Only comment here is that IBM tools tend to be more costly than average ETL tools, but it depends on if the company is an IBM shop.
  • One positive aspect is the company has had not a need to switch ETL tool for years.
  • Upgrading to newer versions of the tool brings flexibility in the tool and up-to-date features in relation to other applications.
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ScreenShots