dbt vs. Red Hat JBoss Data Virtualization

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.

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Red Hat JBoss Enterprise Data Services is a top choice for JEE applications. Even though lots of documentation is available, it's difficult in terms of usability. If the development is more based on Java applications it is a good choice. It provides better installation and integrations.

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• dbt supports version control through GIT, this allows teams to collaborate and track the data transformation logic.
• dbt allows us to build data models which helps to break complex transformation logic into simple and smaller logic.
• dbt is completely based on SQL which allows data analyst and data engineers to build the transformation logic.
• dbt can be easily integrated with snowflake.

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• Data source compatibility: since it is Java, it can connect to anything with a JDBC driver.
• Flexibility: you can configure it however you want, we have it configured to use LDAPS for authentication and have all interfaces encrypted, and setting that up was pretty straight forward.

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• Field-level lineage (currently at table level)
• Documentation inheritance - if a field is documented the downstream field of the same name could inherit the doc info
• Adding python model support (in beta now)

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• Pricing
• User Interface

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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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Support availability and resolution response time make it a better choice.

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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.

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Market value and support extended by Redhat is the winner against Veritas. It has cool features and functionality but still, if your organization is Redhat shop it's better to go for the Jboss option.

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• 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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• It has allowed us to start moving applications independent from their underlying data sources, savings us time and limiting cutover effort.

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