dbt vs. Drools

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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As an open source rule engine and product suite, Drools is well suited for the small and middle scale business to manage and integrate the rules to build the rule-driven system which can process the business-critical data and events to produce the automated decision. It is better to use Drools in the well-secured environment (back-end behind the DMZ), not putting it on the customer-facing front or exposing it directly the to public where may bring direct security risk in the enterprise environment. Drools still needs a lot hardening on the security side.

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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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• Writing rules with business focus
• Rules evolution and maintenance
• separate business logic from program code

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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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• Fusion doesn't support persistence of working memory, which brings some extra high availability risk to our business.
• Guvnor still has a lot room to be implemented, it is not so user-friendly for non-technical people, so a lot of business users complain it is hard to master.
• Rule execution server doesn't even have JMX implemented, hard to be monitored.
• Drools is still lacking support for key Web services standards.

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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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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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I did not participate in drools choice. I can only compare drools with the previous situation which was using nothing.

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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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Independently Invited by TrustRadius

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• The IT department quickly adopted Drools as it is a very good java-based rule engine, which saves a lot of time to meet the project timeline and balanced our business requirements.
• Recently we start considering the OpenRules, which may be more business user-friendly.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info