G2

Rajat G.

Data Eng, Mgmt and Governance Associate

Computer Software

Enterprise (> 1000 emp.)

8/7/2026

"Effortless Azure Integration with Fast, Low-Maintenance Spark"

5/5

What do you like best about Azure Databricks?

Having everything—ETL, SQL analytics, and machine learning—in one platform has saved our team a massive amount of time. The Delta Lake integration is super reliable, and Photon makes running heavy Spark jobs significantly faster. I also love that our data engineers and data scientists can collaborate in the exact same notebooks using PySpark and SQL without constantly exporting data back and forth. Unity Catalog has also made managing permissions across datasets much easier. Review collected by and hosted on G2.com.

What do you dislike about Azure Databricks?

The pricing can scale up surprisingly fast if you don't keep a close eye on compute clusters and auto-scaling rules. It also has a bit of a learning curve for team members who aren't as comfortable with Spark or cloud infrastructure. Occasionally, the workspace UI can feel a little sluggish when navigating through lots of folders and old notebooks. Review collected by and hosted on G2.com.

What problems is Azure Databricks solving and how is that benefiting you?

Before Databricks, we had separate systems for our data warehouse and our machine learning projects, which created constant data sync issues. Databricks solved this by giving us a unified lakehouse architecture. It allows us to build reliable pipelines using Delta Live Tables and track ML models with MLflow in one place, which cut our time-to-production for new data models nearly in half. Review collected by and hosted on G2.com.