Databricks Data Intelligence Platform

What differentiates Databricks Data Intelligence Platform from other similar products?

​As someone who has spent years juggling separate data warehouses for my BI and messy data lakes for my AI projects, I finally realized that the Databricks Data Intelligence Platform is the only tool that actually bridges that gap. For me, it’s not just another database; it’s an ecosystem that makes my data smart by default. In my previous setups, I was constantly moving data from a lake to a warehouse just to run a report, It saves me a massive amount of time and storage costs.

What is your favorite aspect of this product?

the thing that actually makes my life easier every day is not having to jump between five different tools just to get one job done. ​Before I moved everything onto Databricks, my workday was a constant back and forth. I’d be in a warehouse for SQL, then I’d have to export a CSV to a different environment to do some Python or ML work, and then I’d have to pray the permissions matched up in both places. It was exhausting and honestly, a huge waste of time.

What do you dislike most about this product?

I’m a big fan of the platform, but if I’m being totally honest with you, it isn’t all sunshine and rainbows. There are definitely days where I’m cursing at my screen. Sometimes I just want to do something quick and simple, and Databricks feels like overkill. Starting up a cluster even with the newer Serverless options can still feel slower than just pulling up a local spreadsheet or a lightweight SQL editor for a tiny task. It’s built for Big Data, so when I have Small Data, it feels like I’m using a sledgehammer to crack a nut.

What recommendations would you give to someone considering this product?

If you want to avoid the headache of managing virtual machines and cluster sizes, try the Serverless SQL Warehouses first. It feels much more like a traditional cloud warehouse like Snowflake you just run your queries and let Databricks handle the infrastructure. It’s a much gentler way to get your feet wet.

What differentiates Databricks Data Intelligence Platform from other similar products?

It's Lakehouse Architecture that combines data warehousing and data lake capabilities a comprehensive MLOps platform built on MLflow for the full machine learning lifecycle, built-in generative AI features, and a collaborative, multi-language notebook environment for data scientists. This integrated, scalable platform streamlines data and AI workflows, enhances governance, and

What is your favorite aspect of this product?

It's fast ,efficient providing real time solutions to our problems

What do you dislike most about this product?

high costs, especially at scale, and its steep learning curve, particularly for those new to distributed computing or Spark

What recommendations would you give to someone considering this product?

Yes definitely

What differentiates Databricks Data Intelligence Platform from other similar products?

databricks is like the all the raw material is being provided of course with the cost and you can build whatever you want using that raw material. everything single thing is transformable and can be changed in the databrciks so it is important to note that it will also change the way you built the app or data transformation on it.

What is your favorite aspect of this product?

the most favorite aspects of the databricks is that it is configurable no need to comprise in any situation but need to remember that it will also cost the amount of flexibility you want and amount of time you spent. so sometimes it becomes art to understand the things like how to manage and go with the flow in the databricks this is how.

What do you dislike most about this product?

the thing which is most dislike about it that whenever i create the workflow it will just demonstrate the thing in one single place like mix of every workflow either it would be bronze,silver,gold workflow.

What recommendations would you give to someone considering this product?

i would recommend to use databricks only for the transformation of data not for the orchaestartion of pipeline. you can do orchaestration from ADF integrating with databrciks.