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Unified analytics platform
What do you like best about the product?
ACID tansaction support to delta lake.
it is a platform for both data engineering and data science.
flexibility with different tpe of data.
scalability and performance.
Integration with cloud services
collabration features
warehousing for real time or nearly real time data
it is a platform for both data engineering and data science.
flexibility with different tpe of data.
scalability and performance.
Integration with cloud services
collabration features
warehousing for real time or nearly real time data
What do you dislike about the product?
Cost will be the primary concern, that can make serveral firms to go for other optins.
maintenance for the complex deployments
maintenance for the complex deployments
What problems is the product solving and how is that benefiting you?
Impoved performance and scalability in processing the data.
Easier adoption of advance analytics tools.
Helps in Real Time Data processing.
Adopting ACID properties into lakehouse helps in data quality and readability.
Easier adoption of advance analytics tools.
Helps in Real Time Data processing.
Adopting ACID properties into lakehouse helps in data quality and readability.
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A Robust Solution for Big Data Management and Analytics
What do you like best about the product?
I really appreciate how Databricks Lakehouse Platform merges the strengths of data lakes and data warehouses, creating a unified space for handling data tasks. It’s like having the best of both worlds which simplifies data management and analytics significantly. The collaborative notebooks are a cherry on top, fostering teamwork and making iterative development smooth among our data teams. Plus, the high-speed analytics capabilities ensure that data queries and sharing are a breeze, which is crucial for our day-to-day decision-making processes.
What do you dislike about the product?
The initial hill to climb in terms of learning can be a bit steep, especially if you're new to big data platforms. It felt like a slow start, but once past that hurdle, things started to click. The cost factor can be a bit of a pinch, especially for smaller setups or projects on a tight budget. While there's a decent amount of guidance out there, the documentation can sometimes leave you wanting more, especially when you hit complex or unique challenges that require a deeper dive to navigate through.
What problems is the product solving and how is that benefiting you?
Databricks Lakehouse Platform is tackling the headache of juggling between data lakes and data warehouses. It's kind of bundled the two into one neat package, making data management and analytics way less complicated. This fusion is cutting down on the tech pile-up in our projects big time, making it simpler to switch between data engineering and data science chores. When it comes to number crunching, the platform's speedy analytics is making queries quick and data sharing reliable, which is big for our decision-making. The collaborative notebooks are a cool feature too, they're encouraging teamwork and making back-and-forth on development ideas smoother among our data teams. There’s a bit to chew on initially learning-wise and the pricing can sting a little, but the payback in simpler data operations and better teamwork is solid.
Databricks Lakehouse Platform Advantages
What do you like best about the product?
1. Support for ACID transactions, time travelling, versioning
2.unity catalog for access control
2.unity catalog for access control
What do you dislike about the product?
As databricks Lakehouse is built on top of delta lakes, it some times throws errors that are related to storage
What problems is the product solving and how is that benefiting you?
1. Storage and retriving the data and able to perform transformation on huge amounts of data without any hiccups
Experience with databricks
What do you like best about the product?
Capability to run the sql query using spark sql to read the data from containers , which also gives the flexibility to play with data. As we are using spark which is very fast and optimize the sql query which help in getting the outputs very even the volume of data is very huge.
What do you dislike about the product?
I have mostly used azure databricks which some time takes lot of time to get started and and some time it didn't even start.
What problems is the product solving and how is that benefiting you?
Interoperability and no vendor lock-in.
End-to-end support for machine learning and faster AI delivery.
End-to-end support for machine learning and faster AI delivery.
Data quality
What do you like best about the product?
Inbluild authentication authorization/ unity catalog
What do you dislike about the product?
Would be nice if we have proper documentation and notes for every activities in databricks. Not able to get some documents via datsbricks website
What problems is the product solving and how is that benefiting you?
No need of external extraction tool to pull datas from different sources
Advance cloud
What do you like best about the product?
While processing the data from source to destination and accessing verity of data
What do you dislike about the product?
Some more features and streaming data not possible
What problems is the product solving and how is that benefiting you?
Everything is fine but other platforms are advanced now
Databricks - A breath of Fresh air in Big Data
What do you like best about the product?
The best part about the Databricks Lakehouse platform is the integration of traditional, tried and tested big data technologies with a UI that is welcoming, refined and revolutionary!
What do you dislike about the product?
The older ui for the platform had well separated elements for data science, data engineering and SQL Workspace. In an effort to combine them in the sidebar, the new UI tries too hard and ends up as a laggy and chaotic mess.
What problems is the product solving and how is that benefiting you?
the databricks lakehouse platform brings out the best of open source together, stitched beautifully in a notebook based UI that feels welcoming and way less intimidating than a traditional Spark distributions.
The platform has a solution for every data person, including but not limited to a Notebook that works with Scala, Python, R and SQL, a traditional SQL Editor, downloadable datasets and in house visualisations just a click away!
The platform has a solution for every data person, including but not limited to a Notebook that works with Scala, Python, R and SQL, a traditional SQL Editor, downloadable datasets and in house visualisations just a click away!
So user friendly and a platform to make the organization's data value chain delivering value
What do you like best about the product?
unified platform for both BI and AI workload
What do you dislike about the product?
To difficult to keep on track with the evolution pace that platform is growing
What problems is the product solving and how is that benefiting you?
Its helping to realise the paradigm of data-centric AI
Data Lake but combined with Datawarehouse benefits
What do you like best about the product?
It offers ACID transactions which is a massive suppport for data consistency, along with this, the leveraging features such as Time travel and schema evolution comes real handy while builidng a scalable solution. In addition of all above,it reduce data storage costs all while not compromising on powerful distributed programming.
What do you dislike about the product?
With all the features combines, it truly is a powerful tool however, it can be a real challange for new users to master it. For BI users, analysts, who arent skilled with programming, may find it difficult to understand the workflow. Moreover, the community for this tool is currently relatively small and hence minimzing community support.
What problems is the product solving and how is that benefiting you?
The business requires to keep to update powerBI dashboard reports which are ever increasing day by day. As a solution, we are utilizing the lakehouse's ACID, and features such as Schema evolution to clean and transform data and build BI dashboard using the now cleaned data.
This solution has eliminated dependency on our already saturated datawarehouse resources. This has also helped in debugging as all data is processed and resides in one place.Last but not the least, this has reduced costs of our datawarehouse by 20%
This solution has eliminated dependency on our already saturated datawarehouse resources. This has also helped in debugging as all data is processed and resides in one place.Last but not the least, this has reduced costs of our datawarehouse by 20%
Databricks: a perfect data platform for python users
What do you like best about the product?
The UI is build keeping ML and python users in mind, it is very intuitive to use.
What do you dislike about the product?
The speed of processing is slow and could be improved
What problems is the product solving and how is that benefiting you?
Easy integration with python notebooks and big data. The pipeline got much efficient.
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