Appen vs. dbt

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Appen
Score 7.2 out of 10
N/A
The Appen platform combines human intelligence from over one million people all over the world with models to create training data for ML projects. Appen users can upload data to the Appen platform, and they provide the annotations, judgments, and labels needed to help create ground truth for models.N/A
dbt
Score 9.4 out of 10
N/A
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.
$0
per month per seat
Pricing
Appendbt
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Appendbt
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Appendbt
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
Appendbt
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Appen
-
Ratings
dbt
9.7
5 Ratings
15% above category average
Simple transformations00 Ratings9.55 Ratings
Complex transformations00 Ratings9.95 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Appen
-
Ratings
dbt
9.0
5 Ratings
10% above category average
Data model creation00 Ratings9.15 Ratings
Metadata management00 Ratings8.65 Ratings
Business rules and workflow00 Ratings8.05 Ratings
Collaboration00 Ratings9.83 Ratings
Testing and debugging00 Ratings9.55 Ratings
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User Ratings
Appendbt
Likelihood to Recommend
10.0
(1 ratings)
9.6
(7 ratings)
User Testimonials
Appendbt
Likelihood to Recommend
Appen
It is well suited for the users and potential employee who are free of any job perspective and need their free time to be utilized. Users can use their free time to be used for submission of interesting tasks.
Whereas the number of tasks are very less and processing time is also very extensive and recruitment takes time more.
Read full review
dbt Labs
If you can load your data first into your warehouse, dbt is excellent. It does the T(ransformation) part of ELT brilliantly but does not do the E(xtract) or L(oad) part. If you know SQL or your development team knows SQL, it's a framework and extension around that. So, it's easy to learn and easy to hire people with that technical skill (as opposed to specific Informatica, SnapLogic, etc. experience). dbt uses plain text files and integrates with GitHub. You can easily see the changes made between versions. In GUI-based UIs it was always hard to tell what someone had changed. Each "model" is essentially a "SELECT" statement. You never need to do a "CREATE TABLE" or "CREATE VIEW" - it's all done for you, leaving you to work on the business logic. Instead of saying "FROM specific_db.schema.table" you indicate "FROM ref('my_other_model')". It creates an internal dependency diagram you can view in a DAG. When you deploy, the dependencies work like magic in your various environments. They also have great documentation, an active slack community, training, and support. I like the enhancements they have been making and I believe they are headed in a good direction.
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Pros
Appen
  • Project listing
  • Hiring of the potential and qualified users
  • Tracking of the projects
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dbt Labs
  • user experience makes it easy to work with SQL and version control
  • customer success team and the dbt (data build tool) community help establish best practices
  • thorough and clear documentation
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Cons
Appen
  • Selection procedure is bit .
  • The questionnaire need to be reviewed.
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dbt Labs
  • 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
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Alternatives Considered
Appen
Appen offers projects mostly related to my native language and also according to my expertise . It offers very interesting projects to be completed , which requires not very expertise and less time to be completed for each task. It is also very convenient to use after selection for the task and also well rewarding against the time consumed for the task completion.
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dbt Labs
Most ETL pipeline products have a T layer, but dbt just does it better. The transformation is on steroids compared to the others. Also, just allows much more Adhoc solutions for very specific projects. Those ETL tools are probably better on the T part if you don't need too many transforms - also dbt is pretty much free dependent on how you work it, also extremely scalable.
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Return on Investment
Appen
  • It has Positive impact as it provides opportunity for new jobs in my area of expertise.
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dbt Labs
  • Simplified our BI layer for faster load times
  • Increased the quality of data reaching our end users
  • Makes complex transformations manageable
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ScreenShots