Databricks Data Intelligence Platform
Databricks, Inc.External reviews
636 reviews
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Using the Databricks Lakehouse Platform to Manage Data in a Flexible and Cost Efficient Way
What do you like best about the product?
The Databricks Lakehouse Platform makes it easy to manage data governance and handle my data in a flexible and cost-efficient way.
What do you dislike about the product?
The hardest part about using the platform has been the learning curve. But there are training materials available and once you get comfortable, it's great!
What problems is the product solving and how is that benefiting you?
Databricks Lakehouse Platform helps me enable business intelligence and machine learning on my datasets,
Ease of use for EDA and modeling with room for efficiency to improve
What do you like best about the product?
Easy to work with and create derived EDA
What do you dislike about the product?
Version control integration, cluster management/failures, DBR migrations
What problems is the product solving and how is that benefiting you?
Makes it easy for everyone to work with and share the same data to build systems, but it comes at the cost of idle time
Databricks Lakehouse is awesome!
What do you like best about the product?
Databricks offers a full stack solution for any data engineers (MLflow, ApacheSpark, Delta lake). One can you use Databricks for all data needs.
What do you dislike about the product?
Cant wait for Lakehouse IQ to launch which will make it easier for non technical individuals using the platform. Currently it will require some knowledge of data
What problems is the product solving and how is that benefiting you?
Delta lake allows different types of data.
Data + AI Summit
What do you like best about the product?
Scaling applications with databricks, hugging face with marketplace agents.
What do you dislike about the product?
Need to be more user friendly and engaging.
What problems is the product solving and how is that benefiting you?
A data sharing journey through modern data stack.
Great Data Handling & Management platform.
What do you like best about the product?
This tool supports almost all types of data.
Supports even the partially arranged/aligned data also.
Provides a way for better data handling and Management ( like Unified View, graphical view, and Comparision graphs ), which helps in better decision-making.
Supports even the partially arranged/aligned data also.
Provides a way for better data handling and Management ( like Unified View, graphical view, and Comparision graphs ), which helps in better decision-making.
What do you dislike about the product?
Need a specified or specialized consultant to set up the tool because of the adaptability of this tool is complex.
Pricing is high compared to similar tools in the market.
Pricing is high compared to similar tools in the market.
What problems is the product solving and how is that benefiting you?
1) To build a unified portal for Data's unified view: From the legacy application of having data in different places, used this tool to create a unified portal of the data.
2) To integrate with AI and Machine Learning tools: Having the data in a unified way using this tool helps us to integrate with other devices ( But this required some high technical expertise)
2) To integrate with AI and Machine Learning tools: Having the data in a unified way using this tool helps us to integrate with other devices ( But this required some high technical expertise)
Great platform for working collaboratively
What do you like best about the product?
- Ability to edit the same notebook with collaborators
- GitLab compatibility
- Multiple languages supported
- Broad functionality allows most of our digital teams to use it for their own needs
- Spark compute is fast and the amount of processors on a cluster is clear
- GitLab compatibility
- Multiple languages supported
- Broad functionality allows most of our digital teams to use it for their own needs
- Spark compute is fast and the amount of processors on a cluster is clear
What do you dislike about the product?
- UI is constantly changing, and changes are not announced with any leadup
- UI can be buggy - WebSocket disconnects, login timeouts, copy/pasting into incorrect cells
- Pricing structure is a little opaque - DBUs don't have a clear dollar-to-time amount
- Notebook structure isn't perfect for production engineering, better for ML or ad-hoc operations
- UI can be buggy - WebSocket disconnects, login timeouts, copy/pasting into incorrect cells
- Pricing structure is a little opaque - DBUs don't have a clear dollar-to-time amount
- Notebook structure isn't perfect for production engineering, better for ML or ad-hoc operations
What problems is the product solving and how is that benefiting you?
- Maintains access to all of our business data on both AWS and Azure, and can switch between those platforms
- Has an interface for data scientists, engineers, and business users and prevents needing to buy additional tools
- Allows big data applications to run without having to do much Spark configuration
- Has an interface for data scientists, engineers, and business users and prevents needing to buy additional tools
- Allows big data applications to run without having to do much Spark configuration
Built to accelerate development
What do you like best about the product?
I have been using databricks for almost 4 years and it has been a great asset to our development as a team and our product.
Shared folders of re-usable and tracked notebooks allow us to work on tasks only once, minimising duplication of work, which in turn accelerates development cycle.
One of my personal favourites are the workflows, that allowed us to automate a variety of tasks, which availed capacity for us to focus on the right problems at the right time.
Another great selling point for me, is that collaborators can see each other typing and highlighting live.
Shared folders of re-usable and tracked notebooks allow us to work on tasks only once, minimising duplication of work, which in turn accelerates development cycle.
One of my personal favourites are the workflows, that allowed us to automate a variety of tasks, which availed capacity for us to focus on the right problems at the right time.
Another great selling point for me, is that collaborators can see each other typing and highlighting live.
What do you dislike about the product?
UX could be improved
While I appreciate the addition of new features, developments and experiments, the frequency of changes made it tiring and frustrating for me recently.
Too much, too frequently. The 'new notebook editor' is a great example here. The editor itself could be a very useful change, but changing all the keyboard shortcuts at the same time without letting the user know is questionable to me.
I would prefer it, if changes were rolled out less frequently with detailed patch updates (see Dota 2 for example), and configurable options in the user settings.
E.g. I would use the experimental 'new notebook editor' if I could keep the keyboard shortcuts the same.
Less frequent, more configurable updates please.
One of the biggest pain point for me is the Log In and Log Out process. Why does Databricks have to log me out every couple of hours? Especially while I am typing in a command cell?
Could this be improved please?
Also, would love it if libraries on clusters could be updated without having to restart the cluster.
Having said all this, I do love some of the new features, such as the new built-in visualisation tool, however would love it even more if titles could be added and adjusted.
While I appreciate the addition of new features, developments and experiments, the frequency of changes made it tiring and frustrating for me recently.
Too much, too frequently. The 'new notebook editor' is a great example here. The editor itself could be a very useful change, but changing all the keyboard shortcuts at the same time without letting the user know is questionable to me.
I would prefer it, if changes were rolled out less frequently with detailed patch updates (see Dota 2 for example), and configurable options in the user settings.
E.g. I would use the experimental 'new notebook editor' if I could keep the keyboard shortcuts the same.
Less frequent, more configurable updates please.
One of the biggest pain point for me is the Log In and Log Out process. Why does Databricks have to log me out every couple of hours? Especially while I am typing in a command cell?
Could this be improved please?
Also, would love it if libraries on clusters could be updated without having to restart the cluster.
Having said all this, I do love some of the new features, such as the new built-in visualisation tool, however would love it even more if titles could be added and adjusted.
What problems is the product solving and how is that benefiting you?
Databricks is used as the core of our research environment.
It is used to provide quick and efficient analysis of whatever question or problem might arise while keeping the production environment safe and undisturbed.
It is used to provide quick and efficient analysis of whatever question or problem might arise while keeping the production environment safe and undisturbed.
Progressing in the right direction
What do you like best about the product?
Being quickly able to get the environment up and running for any kind of workloads. The support for all three languages and catering to the needs of Data Engineering and ML.
What do you dislike about the product?
Too many customizations are needed to achieve the right mix of parameterization for optimal performance. On the other hand, snowflake provides lots of features out of the box without the developer worrying about these things.
What problems is the product solving and how is that benefiting you?
Managing the intermediate layers and data engineering activities like wrangling/mashing/slicing/dicing of the data well. Greater control of the data via data frames.
Databricks is a very reliable way to run Spark
What do you like best about the product?
Databricks is the most reliable and flexible way to run Spark applications for data engineering workloads.
What do you dislike about the product?
Databricks is at the top end of the market on pricing.
What problems is the product solving and how is that benefiting you?
We use Databricks to run our Spark applications, which process hundreds of terabytes of data, need to be cost-effective, and run in a timely manner.
Make process easy for big data transformation
What do you like best about the product?
It's stores data in delta lake that basically helps to generate a backup of data doesn't matter if process failed every time it took cache of data and most importantly we can easily migrate it with any cloud platform to handle big data.
What do you dislike about the product?
For dislike I would say some time cluster takes time to run and it gives memory error and it's bit costly in use and sometime notebooks cells stuck in between run so team can work on it bit.
What problems is the product solving and how is that benefiting you?
I use it mainly in azure dala lake connection it can easily connect with storage and by applying transformation we can easily push tha data. Most important I use pyspark and sql spark in one notebook meaning we can write script whatever language we want. I use it for etl flow by connecting with azure data factory.
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