Databricks Data Intelligence Platform
Databricks, Inc.External reviews
772 reviews
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Solves Developers’ Problems with Genie, Lakeflow Connect, and DLT
What do you like best about the product?
This platform solves developers’ problems by offering features like Genie, Lakeflow Connect, and DLT.
What do you dislike about the product?
Before using it, I want to understand the compute and charges, and how to use it properly. Basically, I need to learn a lot first.
What problems is the product solving and how is that benefiting you?
It solved our data pipeline and dashboard creation challenges. With SDP and AI/BI Genie, we moved from manually managing the data pipeline to simply declaring it in SQL and having everything handled for us. Instead of spending so much time building dashboards, we can now just ask questions in natural language and get the answers we need without wasting a lot of time.
Intuitive UI and AI-Powered Experience That Keeps Getting Better
What do you like best about the product?
The UI is pretty intuitive and they are using ai to make the experience even better
What do you dislike about the product?
For the most part, it’s a great platform, but some of the debugging options could be improved.
What problems is the product solving and how is that benefiting you?
I use it to write queries for extracting data and running experiments, mostly with SQL and Python.
Scalable, All-in-One Environment with Some Learning Curve
What do you like best about the product?
I like Databricks for its scalability and all-in-one environment for data engineering, analytics, and machine learning. It allows me to process large datasets efficiently while keeping workflows organized in one platform. The scalability is very valuable because it lets me handle growing data volumes and complex workloads without performance issues. As projects expand, the platform can scale resources efficiently.
What do you dislike about the product?
Some features can have a learning curve, especially for new users working with advanced configurations or cluster management. The interface could also be more intuitive in certain areas. The setup was relatively smooth for core features, but some advanced settings like cluster optimization, permissions, and integrations required more time and technical knowledge.
What problems is the product solving and how is that benefiting you?
Databricks solves major data management and analytics challenges by efficiently handling large datasets, simplifying ETL processes, and centralizing workflows. Its scalability allows me to manage growing data volumes without performance issues, ensuring resources scale efficiently as projects expand.
Unifies Data Engineering, ML & Analytics with Ease
What do you like best about the product?
I like how Databricks brings data engineering, analytics, and machine learning into a simple unified platform. I appreciate the faster end-to-end data flow, the single source of truth it provides, and the better collaboration it enables. I also found the initial setup to be quite simple.
What do you dislike about the product?
Cost management is a concern for me. Being a scalable and compute-heavy platform, costs can increase quickly.
What problems is the product solving and how is that benefiting you?
I use Databricks for data processing and engineering, handling large data volumes and eliminating data silos. It unifies data engineering, analytics, and machine learning for faster data flow, providing a single source of truth and improving collaboration.
Fast, Reliable Lakehouse That Unifies Data Processing and SQL
What do you like best about the product?
Data processing and SQL queries are fast and reliable, and the lakehouse platform really helps unify our work.
What do you dislike about the product?
There’s a steep learning curve that demands advanced coding skills and solid Spark expertise, which can make it feel like overkill for teams that only need straightforward SQL reporting.
What problems is the product solving and how is that benefiting you?
We’ve improved our data team’s productivity by removing the need for manual infrastructure management.
Seamless, Scalable Unified Platform for Data, Analytics, and ML
What do you like best about the product?
Its unified platform for data engineering, analytics, and machine learning makes workflows seamless and scalable.
What do you dislike about the product?
It can be expensive and has a bit of a learning curve for new users.
What problems is the product solving and how is that benefiting you?
It simplifies big data processing and analytics in one platform, helping me save time and scale workflows efficiently.
All-In-One Platform That Revolutionizes Workflows
What do you like best about the product?
I love that Databricks combines data engineering, SQL analytics, and machine learning in a collaborative platform. My team and I can clean data, run SQL, and build models all in one place without losing our tasks.
What do you dislike about the product?
The price can get scary fast, and sometimes the cluster startup delay makes me feel like I am waiting for a coffee machine that's still warming up.
What problems is the product solving and how is that benefiting you?
I use Databricks to run SQL, clean data, and build models all in one place, eliminating the need for multiple tools while handling huge data efficiently.
All-in-One Collaborative Platform for Data, ML, and Analytics
What do you like best about the product?
Databricks brings together data engineering, data science, machine learning, and analytics in a single collaborative environment. You don't need to juggle multiple tools for different tasks.
What do you dislike about the product?
Databricks pricing is based on Databricks Units (DBUs), which can be expensive and difficult to estimate upfront. Costs can quickly spiral out of control, especially with auto-scaling clusters.
What problems is the product solving and how is that benefiting you?
Creating a unified lakehouse platform that combines data lakes, data warehouses, and machine learning in one place.
Streamlined Data Processing with Unmatched Speed
What do you like best about the product?
I use Databricks for real-time data ingestion and processing as well as batch processing. I find it easy to use with PySpark, and I appreciate that it serves as a single platform for both real-time and batch processing. The in-memory processing drastically reduces processing time, and working with dataframes makes handling structured data straightforward. I like the fast execution and the ability to clean, massage, and manipulate data all on the same platform. It's also easy to deploy, and I enjoy the smooth CI pipeline with just one click. The initial setup was quite easy, and the product support made it a cakewalk.
What do you dislike about the product?
Databricks should come up with agentic framework integrated, making it a single stop for Data and AI.
What problems is the product solving and how is that benefiting you?
Databricks offers an easy-to-use platform for both realtime and batch processing. It integrates easily with PySpark and supports in-memory processing, significantly reducing processing time. Dataframes make handling structured data simpler.
Databricks Unifies Engineering and Analytics for Scalable Spark Pipelines
What do you like best about the product?
What I like best about Databricks is that it brings data engineering, processing, and analytics into one platform.
From my perspective, it makes it much easier to build and manage scalable pipelines with Spark without worrying too much about infrastructure.
From my perspective, it makes it much easier to build and manage scalable pipelines with Spark without worrying too much about infrastructure.
What do you dislike about the product?
What I dislike about Databricks is that cost control can get tricky if clusters are not managed properly.
Also, debugging distributed jobs is not always straightforward, and sometimes the UI feels a bit heavy when you just want quick insights
Also, debugging distributed jobs is not always straightforward, and sometimes the UI feels a bit heavy when you just want quick insights
What problems is the product solving and how is that benefiting you?
Databricks solves the problem of handling large scale data processing and fragmented tools.
For me, it brings ETL, streaming, and analytics into one place, which reduces pipeline complexity and speeds up development and troubleshooting.
For me, it brings ETL, streaming, and analytics into one place, which reduces pipeline complexity and speeds up development and troubleshooting.
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