dbt vs. Mu Sigma muRx

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
dbt
Score 9.0 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.N/A
muRx
Score 0.0 out of 10
N/A
Mu Sigma headquartered in Northbrook offers muRx, a problem space modeling, analytics planning and data preparation tool designed to support business decisioning and BI processes.N/A
Pricing
dbtMu Sigma muRx
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
dbtmuRx
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
dbtMu Sigma muRx
Considered Both Products
dbt
Chose dbt
dbt is very flexible and can fit into most data pipelines. This is a pro for most organizations that aren't fully bought into one platform (Google Cloud, etc.)
Chose dbt
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.
Chose dbt
I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT …
Chose dbt
Snaplogic is great at the Extraction and Load processes of ETL. It can pull data from anywhere, even behind firewalls. So if you need to get data from various APIs, databases, files, S3, SFTP, etc it is easy to do so. However, it requires special knowledge in order to build …
Chose dbt
I haven't come across anything like DBT before.
Chose dbt
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 …
Chose dbt
Airflow can accomplish the same work as dbt (data build tool), however, dbt's (data build tool) development workflow and UI can open up data transformation and modeling work to non-data engineering teams. Looker might also be able to define data models via LookML with a …
Chose dbt
dbt is great because of its transformation capabilities
muRx

No answer on this topic

Features
dbtMu Sigma muRx
Data Transformations
Comparison of Data Transformations features of Product A and Product B
dbt
9.5
Ratings
15% above category average
Mu Sigma muRx
-
Ratings
Simple transformations10.00 Ratings00 Ratings
Complex transformations9.00 Ratings00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
dbt
9.0
Ratings
12% above category average
Mu Sigma muRx
-
Ratings
Data model creation9.50 Ratings00 Ratings
Metadata management8.50 Ratings00 Ratings
Business rules and workflow9.00 Ratings00 Ratings
Collaboration10.00 Ratings00 Ratings
Testing and debugging8.00 Ratings00 Ratings
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dbtMu Sigma muRx
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All AlternativesView all alternativesView all alternatives
User Ratings
dbtMu Sigma muRx
Likelihood to Recommend
10.0
(0 ratings)
-
(0 ratings)
Usability
9.5
(0 ratings)
-
(0 ratings)
User Testimonials
dbtMu Sigma muRx
Likelihood to Recommend
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.
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Pros
  • 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
  • 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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Usability
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.
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Alternatives Considered
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.
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No answers on this topic
Return on Investment
  • In 3 months we re-wrote the data warehouse (15-20 sources) in dbt with 3 developers.
  • We are using it continually for the past year with no issues.
  • Sorry, I don't have ROI numbers but the impact was huge.
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No answers on this topic
ScreenShots