Positive review for Databricks Lakehouse Platform
Rating: 9 out of 10
IncentivizedUse Cases and Deployment Scope
We currently use the Databricks Lakehouse Platform for a client. My team specifically uses it to data-mine, create reports and analytics for the client. Depending on where the data is stored, various Analytics teams in my company use different platforms - GCP, AWS, Databricks, etc.
Pros
- Scheduling jobs to automate queries
- User friendly - a new user can easily navigate through SQL/Python queries
- Options to code in multiple languages (SQL, Python, Scala, R) and easy to switch with the use of the % operator
Cons
- Errors can be difficult to understand at times
- Session resets automatically at times, which leads to the temporary tables being wiped out from memory
- Git connections are dicey
- Very inconsistent with job success/failure notification emails
Likelihood to Recommend
Databricks is great for beginner as well as advanced coders. The interface is extremely user-friendly and the learning curve is quite short. It is well suited for automation where we can have scripts running late at night when the load is less and wake up to an email notification of success or failure. It is also well suited for writing codes that require the use of multiple languages (in some cases of data modeling)
The ability to store temporary/permanent tables on data lakes is a fabulous feature as well. PySpark is an excellent language to learn and it works really fast with large datasets.
The ability to store temporary/permanent tables on data lakes is a fabulous feature as well. PySpark is an excellent language to learn and it works really fast with large datasets.
Vetted Review
2 years of experience