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
Spyder
Score 8.5 out of 10
N/A
Spyder is a free and open source scientific environment for Python. It combines advanced editing, analysis, debugging, and profiling, with data exploration, interactive execution, deep inspection, and visualization capabilities. Spyder is sponsored by open source supporters QuanSight, and NumFOCUS, as well as individual donors.
$0
per month
Pricing
dbt
Spyder
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dbt
Spyder
Free Trial
Yes
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
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Entry-level Setup Fee
No setup fee
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dbt
Spyder
Features
dbt
Spyder
Data Transformations
Comparison of Data Transformations features of Product A and Product B
dbt
9.7
8 Ratings
17% above category average
Spyder
-
Ratings
Simple transformations
10.08 Ratings
00 Ratings
Complex transformations
9.48 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
The prerequisite is that you have a supported database/data warehouse and have already found a way to ingest your raw data. Then dbt is very well suited to manage your transformation logic if the people using it are familiar with SQL. If you want to benefit from bringing engineering practices to data, dbt is a great fit. It can bring CI/CD practices, version control, automated testing, documentation generation, etc. It is not so well suited if the people managing the transformation logic do not like to code (in SQL) but prefer graphical user interfaces.
Spyder is an open-source Python IDE designed for the movement of data science work. Spyder comes with an Anaconda package manager distribution, so depending on your setup you may have installed it on your machine.
Spyder includes most of the "standard IDE" features you can expect, such as a strong syntax code editor, Python code rendering, and an integrated text browser.
Spyder is used when we want to develop a code that is useful and able to explore proper documentation of the code that has been written. We use Spyder to perform data-related operations like filtration, cleaning, and enhancing the data qualities. There some cases where it is less appropriate like working in an environment, creating dashboards of data visualizations and plots.
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.
It is fairly straightforward to use. Pretty much good to go as soon as you install it. The IDE itself is very user friendly, and it is only limited by whatever limitations Python has as a language. Great for those who want to run their scripts quickly or do some Python programming without fussing.
Most of data scientists or data engineers are either using ec2 on the cloud or Atom or PyCharm locally. It is a bit hard to find people who are still using Spyder and have the sight of the IDE and can help you to answer your question.
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 there's a FREE version for 1 dev seat with no read-only access for anyone else, so you can always start with that and then buy yourself a seat later.
I think Spyder doesn't stack up as well as other IDEs due to its many limitations. But it is available for free and that is one advantage it has over its competitors