I have recently gotten into Databricks and trained on one model. I started using Databricks because of its hardware support and all the other things that it provides, and it is easier to get into. Earlier, when I had to test some part of my code or test if it was working or not, it was not just a fair, not a full production run, but just a fair testing; I had to get a machine, raise a request, get into the whole process. With Databricks, I can just simply create one myself. I could get the resources, whatever they are required, test it out all there, and then go ahead with that, and that is why I have been using it primarily.
Databricks Data Intelligence Platform
Databricks, Inc.External reviews
628 reviews
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External reviews are not included in the AWS star rating for the product.
Streamlining Data Science and Machine Learning Workflows with Databricks Platform.
What do you like best about the product?
What I love most about Databricks Data Intelligence Platform is how user-friendly it is. From easy implementation to excellent customer support, I find myself using it daily without hassle. Its extensive feature set and seamless integration with other tools make my work so much smoother.I also loved how it solved most of the major problems that we use to face as data engineers and ml engineers
What do you dislike about the product?
I find Databricks Data Intelligence Platform a bit challenging to pick up at first, especially if you're new to big data and cloud technologies. Sometimes, navigating through its advanced features can feel a bit overwhelming and less straightforward
What problems is the product solving and how is that benefiting you?
Databricks Data Intelligence Platform has revolutionized my workflows by seamlessly integrating data engineering and machine learning tasks.
Its scalability ensures I can handle large datasets and complex computations with ease, boosting my productivity.
Collaboration features like shared notebooks facilitate real-time teamwork, enhancing our ability to iterate and innovate together.
Built-in support for Apache Spark and ML libraries empowers me to perform advanced analytics and develop sophisticated models efficiently.
Automated infrastructure management saves time and allows me to focus on delivering impactful insights and solutions.
Its scalability ensures I can handle large datasets and complex computations with ease, boosting my productivity.
Collaboration features like shared notebooks facilitate real-time teamwork, enhancing our ability to iterate and innovate together.
Built-in support for Apache Spark and ML libraries empowers me to perform advanced analytics and develop sophisticated models efficiently.
Automated infrastructure management saves time and allows me to focus on delivering impactful insights and solutions.
Best review
What do you like best about the product?
It's very helpful and working smoothly
Anyone can access these platform which is the main point
Anyone can access these platform which is the main point
What do you dislike about the product?
Need to provide more free content and always notify users before any event
What problems is the product solving and how is that benefiting you?
My organisation is a partner so I am using this as my daily to daily activity that's really helpful
A well thought out evolving data platform
What do you like best about the product?
The constant evolution of the platform, with customer focused additional features, backed by knowledgable employees and a great community.
What do you dislike about the product?
The providers in the marketplace could be better or a superset of those in Snowflake - would make some migration discussions easier
What problems is the product solving and how is that benefiting you?
It provides a comprehensive platform for data pipelineing, storage and consumption.
Best Online data management platform for AIML
What do you like best about the product?
With datbricks we can manage our all data without any hassle and also they have number of certification courses that provide full guides and new technologies knowledges in affordable and cheap price. Their ease to use interface make them reliable and ease to implementation.
What do you dislike about the product?
With Databricks we get a support inour carrer with their AIMLlearning platform and also they have best tools and integration where we can manage all the data very easily and use them frquently on daily basis.
What problems is the product solving and how is that benefiting you?
Overall with Databricks we can workonmultiple techonolgies related Big data or data science. They have option for ETL and data warehouses and also they have MLOps Platform where we learn new technologies. Their user dashboards and interface make them more reliable and ease to use for us.
Best ETL tool for Data Engineers
What do you like best about the product?
Very fantastic and great platform for data management solution. They have very reliable tools and features that make my work more easier and also their ease to implement features gives reliable and frequent result as we want.
What do you dislike about the product?
Thei integartion is very supportive and good in use. Databricks have the best user interface where we experience reliable and secure platform for data mangement.
What problems is the product solving and how is that benefiting you?
Databricks is the most useful platform for big data analysis and also we can learn more about machinelearning with their ML section where we can develop number of projects very easily. Databricks have option of data warehouse and ETL tool and also their secure platform gives a reliable services.
Lead Developer
What do you like best about the product?
its good tool to load data and extracts everyday
What do you dislike about the product?
it is little bit expensive for spark cluster and their applications
What problems is the product solving and how is that benefiting you?
their way of data governance and everything in the same place
services are easy to implement at scale
What do you like best about the product?
I like the Delta lake model, cool features are incremental data updates, change data capture, and streaming data can be done under the hood.
What do you dislike about the product?
sharing the data out of azure has some limitations.
What problems is the product solving and how is that benefiting you?
building data lake using delta lake. Storing wide variery of data and applying data cleaniess, and performing aggregations as needed.
High speed Data Management tool
What do you like best about the product?
Databrics givs a very high speed and effective experienceto manage the huge data without any complexcity. They have number of features and ease to use interface that make them very reliable and user friendly.
What do you dislike about the product?
We use databrics frequently in our company for data mangement.Their ease to use interface gives hassle free solution and great customer suport. We can very easily implement their templates and custom dataset to integrate our project and work on them.
What problems is the product solving and how is that benefiting you?
It is the best ETL tool and their pipelines make the data very friendly and ease to manage. They have multiple features like data warehouse, big data analysis and MLOps platforms etc. Their echo friendly system make them more useful and user friendly data management solution for us.
Provides resources to users quickly without much hassle
What is our primary use case?
What is most valuable?
The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle.
What needs improvement?
I think setting up the whole account for one person and giving access are areas that can be difficult to manage and should be made a little easier.
For how long have I used the solution?
I have experience with Databricks.
What do I think about the stability of the solution?
I think there's a duration after which our training without any activity would expire, which I think is a fair point, and that is the only place where I think this will stop. I haven't come across a lot of problems with Databricks.
What do I think about the scalability of the solution?
The tool is not used as frequently as PyTorch. I don't know why I am comparing Databricks to PyTorch, but I think around five people use it.
How are customer service and support?
I have not contacted the solution's technical support team.
Which solution did I use previously and why did I switch?
Before Databricks, I used to use a cloud support platform.
How was the initial setup?
The solution is deployed on the cloud.
Which other solutions did I evaluate?
I chose Databricks over other products, considering the hardware support it offers.
What other advice do I have?
A little bit of time will be needed to get comfortable with Databricks.
I rate the tool an eight out of ten.
Leveraged the Databricks Data Intelligence Platform for streamline data processing and analytics.
What do you like best about the product?
What I like best about Databricks Data Intelligence Platform:
The seamless integration of big data and machine learning workflows, enabling efficient data processing, collaborative development, and scalable analytics in a unified environment
There are numerous upsides but I will go with my top THREE:
1. Scalability: Automatically scales resources to handle large data volumes efficiently.
2. Collaborative Environment: Supports collaborative development with shared notebooks and real-time co-authoring.
3. Unified Analytics: Combines data engineering, data science, and machine learning in a single platform.
The seamless integration of big data and machine learning workflows, enabling efficient data processing, collaborative development, and scalable analytics in a unified environment
There are numerous upsides but I will go with my top THREE:
1. Scalability: Automatically scales resources to handle large data volumes efficiently.
2. Collaborative Environment: Supports collaborative development with shared notebooks and real-time co-authoring.
3. Unified Analytics: Combines data engineering, data science, and machine learning in a single platform.
What do you dislike about the product?
I can only suggest a more robust and technical customer support.
What problems is the product solving and how is that benefiting you?
Several problems are solved but I will limit my response to three:
1. Complex Data Processing: It simplifies the handling of large and complex datasets by leveraging Apache Spark, enabling faster data processing and analysis.
2. Unified Environment: It provides a unified platform for data engineers, data scientists, and analysts to collaborate seamlessly on data projects, reducing silos and improving productivity.
3. Scalability: The platform automatically scales resources based on workload demands, ensuring efficient resource utilization and performance even with varying data volumes.
1. Complex Data Processing: It simplifies the handling of large and complex datasets by leveraging Apache Spark, enabling faster data processing and analysis.
2. Unified Environment: It provides a unified platform for data engineers, data scientists, and analysts to collaborate seamlessly on data projects, reducing silos and improving productivity.
3. Scalability: The platform automatically scales resources based on workload demands, ensuring efficient resource utilization and performance even with varying data volumes.
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