Databricks Data Intelligence Platform
Databricks, Inc.External reviews
637 reviews
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A Game-Changer for Data Teams
What do you like best about the product?
I am using data bricks from around 1 year. In a week I use it approx 3-4 days. Everything is integrated, which means I don’t have to switch between multiple tools to do different tasks. It really improves team collaboration. Sharing notebooks and collaborating on models is super easy. This has been great for our team since we often work together on projects and need to see each other's code and progress.
What do you dislike about the product?
This is probably the biggest downside. Databricks can get pretty expensive, especially if you’re not monitoring your usage carefully. It’s definitely a platform that’s best suited for teams with a larger budget or organizations that need heavy-duty data processing.
What problems is the product solving and how is that benefiting you?
Managing and processing huge volumes of data used to be a huge headache. As our data grew, our previous tools were struggling to keep up. Databricks has solved this by providing a robust, scalable infrastructure that automatically adjusts to handle large datasets. Whether it’s batch processing or streaming data, we no longer worry about performance issues when scaling up.
A blend of AI powered platform for data management
What do you like best about the product?
>Leverage AI features like LLM and Generative AI to manage data intelligently and generate actionable insights
> Powerful data management capability like ETL , data processing to generate clean data
> Easy to implement pipelines and a great customer network
> Powerful data management capability like ETL , data processing to generate clean data
> Easy to implement pipelines and a great customer network
What do you dislike about the product?
> Use can be limited to a specific use case
> Limited number of connectors to integrate data to other BI tools for reporting purpose
> Support network can be tedious
> Limited number of connectors to integrate data to other BI tools for reporting purpose
> Support network can be tedious
What problems is the product solving and how is that benefiting you?
> Security of data and systems using AI features
> Scalable solutions for managing data as data lake and AI features can be leveraged
> Scalable solutions for managing data as data lake and AI features can be leveraged
It's super handy for analytics, scales well, and you can easily rely on it.
What do you like best about the product?
The best thing about Databricks is that it very easily consolidates data engineering, data science, and analytics – all in one place Therefore, I can process huge data sets quickly, run very complex machine learning operations, all without switching tools. Collaboration through notebooks with my team in real-time really reduced a lot of back and forth that I used to have.
What do you dislike about the product?
The big issue is pricing can quickly ramp up if I’m not careful with cluster size or if I forget to turn them off. I had to learn how to use some of the more advanced features, like Unity Catalog and MLflow connectors if I was to use them well. The only thing I would add is an easy interface, like in some BI products. It may be overwhelming for the newbie.
What problems is the product solving and how is that benefiting you?
I can construct fraud detection models, run queries over billions of rows, and test proof-of-concepts for clients all on one platform. This cost me days in setting work up. Huge workloads on peak hours will not slow me down as I can scale my computing power instantly. This is why I think Databricks gives me more freedom to play around with data models and machine learning at scale as compared to Snowflake or any other alternative.
Brings together data engineering, analytics & machine learning into a single integrated platform.
What do you like best about the product?
Databricks brings together data engineering, analytics, and machine learning into a single, integrated platform, reducing the need for separate tools and simplifying workflows.
What do you dislike about the product?
Some users find the platform challenging to learn, especially for those unfamiliar with distributed computing or specific Databricks features.
What problems is the product solving and how is that benefiting you?
Databricks reviews mention its Delta Lake architecture and governance features help ensure data reliability and security.
Great platform for big data and ML, with some learning curve
What do you like best about the product?
What I really like about Databricks is how it brings everything—data engineering, analytics, and machine learning—into one place. It saves a lot of time when switching between workflows. The collaborative notebooks are super handy when working with a team, and the Spark integration just works without much hassle. Delta Lake is also a plus—being able to manage large datasets with versioning and ACID support is honestly a lifesaver in production scenarios.
What do you dislike about the product?
The platform can feel a bit intimidating at first, especially if you're new to big data tools. Setting up clusters and understanding the pricing model took me a while. Also, the UI sometimes lags when you're dealing with large notebooks or switching between multiple tabs. I wish the onboarding was a bit more beginner-friendly
What problems is the product solving and how is that benefiting you?
Databricks helps us streamline our entire data pipeline — from ingestion to analytics to machine learning. Earlier, managing large-scale datasets and running ML models used to be fragmented across tools, but Databricks made it way smoother. It saves us a lot of dev time and reduces the friction between data engineering and data science teams. Having everything in one place also makes debugging and scaling much easier.
Make your Data solid BRICK with Databricks
What do you like best about the product?
What I like the best about Databricks data intelligence platforms is the uninterrupted integration of data engineering, data science and AI workflows on an single platform, which improves cooperation, robustness and performance for large data and ML projects.
What do you dislike about the product?
The lowest useful aspect of Databricks data intelligence platform is its complication for new users and steep learning state, especially for those without a strong background in spark or distributed computing. Additionally, it can be expensive on a scale, and debugging large workflows can sometimes be challenging due to limited transparency in error tracing.
What problems is the product solving and how is that benefiting you?
Databricks solves the problem of silent data and fragmented devices by providing integrated environment for intelligence platform data engineering, analytics and machine learning. It enables rapid data processing, real -time cooperation, and streamlined workflows, eventually improves decision making and intensifies innovation in teams.
I really like the seamless and intuitive UX
What do you like best about the product?
Thatvamanybdifferent things are somehow centrally orchestrated. All of the features right in my hand!
What do you dislike about the product?
Not much! Inthink that almost everything is at leastbin an acceptable level
What problems is the product solving and how is that benefiting you?
N/a
Databricks Summit
What do you like best about the product?
Interactive and very user friendly easy use
What do you dislike about the product?
Not much to say but making it very easy for developers
What problems is the product solving and how is that benefiting you?
Moving away from legacy on prem systems to cloud based solutions.
Great event to ramp up quickly
What do you like best about the product?
The connectivity of all the experiences .
What do you dislike about the product?
The embedded experience is not mature enough to just consume parts of the platform
What problems is the product solving and how is that benefiting you?
Shipping an embedded data lake
Amazing Data Intelligence Platform
What do you like best about the product?
It’s a super collaborative tool where all member of the data team can easily work together
What do you dislike about the product?
Learning curve is quite steep and there’s a lot going on
What problems is the product solving and how is that benefiting you?
Having a collaborative tool for building out ML workflows and scalability
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