dbt vs. Hevo Data

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

Hevo Data is professionally sound in data management and credible analytical processes, where there is proper sourcing and data connectivity, from the different sources. Further, Hevo Data brings huge transformation and analytical approaches, which increases the viability of every operation in the company, and results are credibly issued. The integration that Hevo Data provides is comprehensively sound, and it gives quality coordination.

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

• 5 Minute Sync with Salesforce
• Transformations
• Auto Schema Mapping
• Push to Salesforce

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

• If we are getting data from other sheets then sheet which is connected to Hevo Data doesn't updates in real-time.
• Hevo Data change time in it's workbench on its own. For e.g. If our database timestamp is in UTC format then Hevo Data will automatically change the time to IST but if I run the same code outside the Hevo Data workbench then time is still in UTC. This creates lots of confusion while working on Hevo Data.

Incentivized

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

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

1. Cost efficient 2. Creation of automated pipeline 3. Can load data from multiple data sources 4. Updates data in near real-time - We were able to get near real time insights from the data model which we have created in hevo 5. It has good integration with different BI tools

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

• Increased Time
• Decreased Failures
• Increased User Happiness

Incentivized