dbt vs. SAS Data Management

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.

Incentivized

SAS/Access is well suited for companies who need to manipulate and analyze large databases and data-sets. It does the same thing as SQL, and if you already know basic SAS coding it is easier to pick up. SAS/Access works well with analyzing data from multiple data-sources at once, including large databases stored in external and virtual environments like Hadoop. Data can be easily reassembled from relational databases for use by the user. SAS/Access is not necessary if you are only pulling data from one database that you have the physical file for.

Incentivized

• 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

• SAS supports the main database connection options that allow you to optimize the performance of your extracts and loads.
• Simplicity of the syntax for a basic connection.
• Ability to configure by an administrator in a BI environment so that all users can benefit from the connection without having to establish it by themselves.

Incentivized

• 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

Incentivized

• It is a versatile product but sometimes difficult to use due to the very close link with the proprietary programming language where specific knowledge is required.
• Compared to competitors on the market that offer the same functions for the integration perimeter, it is certainly very expensive.
• It is very simple to use when combined with products from the SAS suite, less so it is being used stand-alone or integrated with other well-known brands.

Incentivized

We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.

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.

Incentivized

The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.

Incentivized

It worked as expected.

Incentivized

With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.

Incentivized

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.

Incentivized

Because SAS Data Integration Studio is the third party it seems to work equally well with all our systems. That is to say that it doesn't really work better with Microsoft or Oracle but really just seems to work equally well with all of them. It has a very powerful back-end that allows us to transform and load our data quickly and efficiently programmer time wise.

Incentivized

• 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.

Incentivized

• The platform enabled us to have a single repository of customers to run campaigns on.
• Feedback from various campaigns is stored in a single database, which makes running A/B analysis easier.
• Helped improve data quality due to SAS Dataflux being a part of the SAS Data Management Platform.

Incentivized