kotomama
Boston
4.0
Support responded quickly
Had an issue with cluster scaling, but support helped fast.
lucy_m
Denver
4.0
Good platform but UI needs work
I appreciate the solid data engineering tools but the interface isn’t super intuitive. Had to spend extra hours training the team. Still, the end results justify the effort.
samantha_j
Houston
4.0
Works well for big data
Handles large datasets without crashing.
mark_w
Philadelphia
4.0
Solid platform with minor glitches
Databricks offers great scalability and integration options. Occasionally the notebook execution stalls and requires a restart. Still, it’s our go-to for complex data projects.
trader_ru
San Francisco
4.0
Stable and efficient platform
Databricks handles big data jobs without hiccups.
Morgan
Austin, TX
4.0
Mostly Solid but Some Bugs
I've been using Databricks for about six months now to manage our ETL pipelines and collaborative analytics. The platform really speeds up data workflows with its integration of Apache Spark, which is a huge plus for our team. However, I've noticed occasional delays during peak hours and some glitches with notebook collaboration that slow us down. Support has been helpful but sometimes slow to respond when these issues pop up. it's boosting our productivity, just hoping they improve the collaboration features soon.
anna_lee
Portland
4.0
Good value for data teams
Our analysts found the collaborative features very helpful. The platform supports multiple languages which is a big plus. Wish the mobile app was more polished though.
michael_b
Atlanta
4.0
Powerful but with a learning curve and quirks
Started using Databricks about six months ago for building ML models. Initially, the documentation was a bit overwhelming especially for new data scientists on our team. We faced some trouble configuring the cluster autoscaling which caused downtime during our peak loads. However, once we got past those hurdles, the collaborative notebooks and integrated workflows significantly boosted our productivity. The platform’s ability to handle streaming data pipelines is impressive, though sometimes the UI responsiveness lags when running heavy queries.
julia.k
Seattle, WA
4.0
Great for data engineering workflows
Databricks' platform has made it much easier to run large-scale Spark jobs in the cloud. The UI is clean, and setting up clusters doesn't take forever like on other platforms I tried. A bit pricey though, which is the only downside for me.