Alteryx Designer Cloud vs. dbt

For doing ETL and data transformations where your data is already in a cloud environment Alteryx Designer Cloud is ideal. It allows for the continued democratisation of data and analytics to permeate more extensively throughout a business, particularly those that are already in the cloud or have cloud services in place and are comfortable with procurement and consumption of these systems over and above desktop software. The ETL processing for data validation and wrangling uses machine learning to enable highly efficient data manipulation which saves lots of time and this is a distinct advantage over the desktop software. The expansion and integration of other Alteryx cloud services such as ML, Metrics Store and App builder will only strengthen this position

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.

Incentivized

• Gives automatic options for code.
• Allows for notes on code.
• Duplicates work and allows for repurposing work.

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

• Hadoop source data tables are presented in a flat searchable list but I would rather see them in the native hierarchy.
• Web interface can be flaky. We often need to refresh the page.

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

Our IT group presented Trifacta to me. They picked it out and among the crowd for me. This was way beyond ETL tools, SQL, or any programming language. It's just much faster and because it's sitting on Hadoop you bypass some of the slowdowns typically faced with RDBMS.

Incentivized

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.

Incentivized

• Increased productvity by 5x
• Reduced costs of running and patching desktop and server based software entirely

• Simplified our BI layer for faster load times
• Increased the quality of data reaching our end users
• Makes complex transformations manageable

Incentivized