DBT (Data Build Tool) and Blast are both open-source tools that help data analysts and engineers transform, test, and analyze data in their warehouses. While both tools have similar features and functions, there are some key differences between the two.
One of the main differences between DBT and Blast is the programming language support. DBT is a SQL-only tool, while Blast can run any language, including Python and R. This makes Blast a more versatile option for users who need to use a variety of languages in their data pipelines.
Another difference between the two tools is the pricing model. DBT Cloud charges users a per-seat fee, while Blast bills users based on the execution time of their queries. This can make Blast a more cost-effective option for the companies with especially big teams.
Both DBT and Blast provide data testing functionality, but Blast goes a step further by integrating data tests into the pipelines and allowing users to mark a task as failed and prevent the pipeline from continuing if the test fails. This can help users ensure the integrity of their data and catch errors before they become a bigger problem.
Both tools also provide a data catalog feature, which allows users to document and organize their data assets. On top of that, Blast can visualize your SQL queries to have a better understanding of the query flow.
DBT has a larger community and more resources available, so it may be a better option for users who need more support and guidance. On the other hand, Blast provides premium support to early adopters including customization of the feature set and the cloud deployment to accomodate the needs of the business.
Which tool is right for your organization?
Deciding between DBT and Blast ultimately comes down to your organization's specific needs and requirements. Here are a few factors to consider when making your decision:
Cost: If you have small team, DBT's per-seat pricing model may be more cost-effective for you. On the other hand, if you have a larger team, Blast's pay-per-task model may be a better fit.
Language support: If you are sure you will not need more than SQL in your data pipeline, DBT may be the better choice. If you use a wide range of languages, Blast may be more flexible.
|Programming language||SQL only||Any language (e.g. Python, R)|
|Pricing model||Per-seat||Execution time of queries|
|Data Quality||Yes, simple||Yes, advanced functionality|
|Community / resources||Large community and resources||Smaller community, premium support|
In conclusion, both DBT and Blast are valuable tools for data professionals, but the choice between the two will depend on the specific needs and preferences of the user. DBT is a SQL-only tool with a large community and extensive resources, while Blast is a more versatile option with a cost-effective pricing model and advanced data testing functionality. Blast also offers premium support to early adopters, including customization of the feature set and cloud deployment to accommodate the needs of the business. Users should carefully consider their specific needs and budget when deciding which tool is the best fit for their organization.