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.
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dbt
Score 9.0 out of 10
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dbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.
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Pricing
AWS Data Exchange
dbt
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
AWS Data Exchange
dbt
Free Trial
No
Yes
Free/Freemium Version
No
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
AWS Data Exchange
dbt
Features
AWS Data Exchange
dbt
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
dbt
-
Ratings
Connect to traditional data sources
7.00 Ratings
00 Ratings
Connecto to Big Data and NoSQL
9.00 Ratings
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
dbt
9.0
Ratings
12% above category average
Data model creation
9.00 Ratings
9.50 Ratings
Metadata management
9.00 Ratings
8.50 Ratings
Business rules and workflow
7.00 Ratings
9.00 Ratings
Collaboration
9.00 Ratings
10.00 Ratings
Testing and debugging
7.00 Ratings
8.00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
AWS Data Exchange
7.0
Ratings
15% below category average
dbt
-
Ratings
Integration with data quality tools
7.00 Ratings
00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
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.
dbt (Data Build Tool) is best suited for doing the data transformation. dbt is just a transformation tool and it is not suitable for building a data pipeline which requires extraction of data and loading. dbt is well suited for SQL based transformation logic and it is less appropriate when transformation logic requires python.
Slow load times of the dbt cloud environment (they're working on it via a new UI though)
More out-of-the-box solutions for managing procedures, functions, etc would be nice to have, but honestly, it's pretty easy to figure out how to adapt dbt macros
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.
dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.
Matillion is graphical versus dbt, which is SQL code-based (that, of course, is a matter of personal preference and not an objective advantage). The integrated testing, documentation generation, lineage, etc., were additional criteria that led us to choose dbt.