dbt simplifies the process of building a solid data pipeline by offering a lot of features that would be difficult to implement from scratch. In particular, the SCD2 and incremental functionality helps remove a lot of overhead for developers and makes ongoing maintenance easier. There are also many other features that are great and contribute to a smoother overall workflow.

I use Fivetran for end-to-end data integration and love how easy it is to get data into our warehouse for analytics, especially as a small data team. It takes little effort, which is crucial for us. I appreciate the wide list of connectors they offer, which really expands our integration capabilities. HIPAA compliance is imperative for us as a healthcare company, and Fivetran meets this need. I also found the initial setup to be very easy.

I have been using DBT every day in my project for the last two years, and I can say it is one of the best platforms for creating data models through SQL-based data transformations. DBT’s ease of integration has helped us save effort during code deployment. We integrated DBT with Git so we can work in parallel on multiple tasks across multiple models for a single requirement. Its ease of implementation also makes it simpler to understand DBT’s benefits and has helped improve our efficiency. The command-line interface and the IDE environment make it easier for us to manage data and execute data models. DBT also has its own test case preparation features, which help us validate both our data model changes and the data being populated through DBT models. If we run into any product-related issues, there is a customer support team that is always ready to guide us through our blockers.