We use the solution for data analytics of industrial data.
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a comprehensive review of Databricks
What do you like best about the product?
its a platform for storing and maintaining data also to manage and process big data.also implementation of apache spark
What do you dislike about the product?
databricks UI complexity.it can be improved to easy use
What problems is the product solving and how is that benefiting you?
databricks platform resolves data complexity by giving i unified platform that integrates with various data sources also it fosters collaborative analytics
A scalable and cost-effective solution that has excellent translation features and can be used for data analytics
What is our primary use case?
What is most valuable?
We extensively use the product’s notebooks, jobs, and triggers. We can create activities. Wherever translation is required, we use Databricks. The product fulfills our customer requirements. It is a cost-effective solution.
What needs improvement?
The product should provide more advanced features in future releases.
For how long have I used the solution?
I have been using the solution for six months.
What do I think about the stability of the solution?
Our data was not too huge. It worked well. It is easily adaptable.
What do I think about the scalability of the solution?
The tool is scalable. We can make it available for a larger audience.
How was the initial setup?
The initial setup is not that difficult. I rate the ease of setup a seven out of ten. The solution is cloud-based. We use native services like Data Factory for orchestration. Sometimes, the customers require us to use Amazon as the cloud provider instead of Azure.
What's my experience with pricing, setup cost, and licensing?
The pricing is average.
What other advice do I have?
There are many services which are coming up. They are still in the preview stage. Overall, I rate the product an eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Microsoft Azure
Databricks, a rising hero for your complex data problems!
What do you like best about the product?
The ease of working at a cloud based data system (compatible with Azure/AWS/GCP) is far more better than those slow, laggy, boring legacy data warehouse systems like hadoop and others. Due to its Spark engine based built, big data processing is speedy, efficient and scalable.
Its a go to solution to my data warehouse / data lake based problems, the best of both worlds. One can integrate variety of data sources/formats like SQL-NoSQL, excel, csv, streaming data, APIs,etc. One can use a feature called Autoloader that eases our implementations of detecting and loading any kinda data in Delta Lake tables without any hard coding.
The platform is designed in such a way that in my 1 year of daily usage I haven't faced any kind of unexpected downtime/issue on platform for which I have to reach out to their customer support group.
I would highly recommend Databricks Lakehouse Platform to anyone who is looking for a powerful and flexible analytics platform.
Its a go to solution to my data warehouse / data lake based problems, the best of both worlds. One can integrate variety of data sources/formats like SQL-NoSQL, excel, csv, streaming data, APIs,etc. One can use a feature called Autoloader that eases our implementations of detecting and loading any kinda data in Delta Lake tables without any hard coding.
The platform is designed in such a way that in my 1 year of daily usage I haven't faced any kind of unexpected downtime/issue on platform for which I have to reach out to their customer support group.
I would highly recommend Databricks Lakehouse Platform to anyone who is looking for a powerful and flexible analytics platform.
What do you dislike about the product?
Browsing and accessing is a bit confusing if one is working on a resource group accounts which could have several main and segregated user based notebooks/files, accessing them is tideous task as a developer, one has to open a seperate new tab just for browsing or opening a seperate file/notebook for referencing puposes. Another thing is the frequency of UI changes in every few months, once a person gets comfortable/used to, a new UI update would pop up making it difficult for a person to adapt these changes once again.
What problems is the product solving and how is that benefiting you?
From its suit of features, it helped me processing daily arriving data from APIs and CSVs from a railway networking website platform, turing it into an Analytical solution in form of dashboard KPIs which play a vital role in taking key decisions and maintaining a lossless on-schedule railway network for real world users of the web product. It has helped me and my team in reducing operational overhead cost with its performance and reliability featues like data versioning and schema enforcement. It has also facilitated collaboration and communication in my team who are working from different corners of world remotely.
It is very useful platform and user friendly platform
What do you like best about the product?
It is very useful platform and user friendly platform
What do you dislike about the product?
It is very useful platform and user friendly platform and it is very easy to implement. There are lots of features.
What problems is the product solving and how is that benefiting you?
It's very useful for ETL platform
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 - 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!
A Tool Box to the Modern Big Data Data Scientist
What do you like best about the product?
The upscale in storing and retrieving large quantities of data with its sdk to s3. In addition, great resources allocation support and additional tools such as clearml.
What do you dislike about the product?
The compatibility to pandas is lacking due to the fact that it is mainly used by me with pyspark which didnt allow an optimal usage for the various pandas libraries.
What problems is the product solving and how is that benefiting you?
Retrieving and querying a very large data warehouse on s3 (several hunders of T'). Performing basic filtering and quering on the data and running a ML experiment on huge amounts of data.
Processes large data for data science and data analytics purposes
What is our primary use case?
It's mainly used for data science, data analytics, visualization, and industrial analytics.
What is most valuable?
Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours.
So that's why it's quite convenient to use for data science, for training machine learning models. By using more computing power, you can make it even faster.
What needs improvement?
There is room for improvement in visualization.
For how long have I used the solution?
I used it for two years. I worked with the latest update.
What do I think about the stability of the solution?
I would rate the stability a nine out of ten. I didn't face performance drops.
What do I think about the scalability of the solution?
I would rate the scalability an eight out of ten.
How are customer service and support?
Databrick's support is great. If we need any support, they are very quick with it. And they genuinely want you to use Databricks. So, whatever we ask them, they come up with multiple solutions to problem statements. That's really good.
Overall, the customer service and support are very good.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I personally prefer using Databricks. However, we also considered using Snowflake, but the pricing was different. It's price per query.
So, as per your storage, a data scientist or a data analytics team needs to query again and again, which does not suit a data-heavy organization.
What was our ROI?
It's a good return on investment for Databricks from a delivery perspective. Delivered multiple dashboards. So, it's quite a good return on investment. And being a small organization, everyone can use Databricks, and cost-wise, it's also good for small organizations.
Which other solutions did I evaluate?
If the company is a startup, Databricks might be suitable. If a big company needs a lot of storage, Teradata might be best for them. It depends on the situation.
What other advice do I have?
Overall, I would rate the solution a eight out of ten. I would definitely recommend this solution for small organizations.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
An easy to setup tool that provides its users with an insight into the metadata of the data they process
What is our primary use case?
My company uses Databricks to process real-time and batch data with its streaming analytics part. We use Databricks' Unified Data Analytics Platform, for which we have Azure as a solution to bring the unified architecture on top of that to handle the streaming load for our platform.
What is most valuable?
The most valuable feature of the solution stems from the fact that it is quite fast, especially regarding features like its computation and atomicity parts of reading data on any solution. We have a storage account, and we can read the data on the go and use that since we now have the unity catalog in Databricks, which is quite good for giving you an insight into the metadata of the data you're going to process. There are a lot of things that are quite nice with Databricks.
What needs improvement?
Scalability is an area with certain shortcomings. The solution's scalability needs improvement.
For how long have I used the solution?
I have been using Databricks for a few years. I use the solution's latest version. Though currently my company is a user of the solution, we are planning to enter into a partnership with Databricks.
What do I think about the stability of the solution?
It is a stable solution. Stability-wise, I rate the solution an eight to nine out of ten.
What do I think about the scalability of the solution?
It is a scalable solution. Scalability-wise, I rate the solution an eight to nine out of ten.
My company has a team of 50 to 60 people who use the solution.
How are customer service and support?
Sometimes, my company does need support from the technical team of Databricks. The technical team of Databricks has been good and helpful. I rate the technical support an eight out of ten.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup phase of Databricks was good. You can spin up clusters and integrate those with DevOps as well. Databricks it's quite nice owing to its user-friendly UI, DPP, and workspaces.
The solution is deployed on the cloud.
The time taken for the deployment depends on the workload.
What's my experience with pricing, setup cost, and licensing?
I cannot judge whether the product is expensive or cheap since I am unaware of the prices of the other products, which are competitors of Databricks. The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts.
What other advice do I have?
It is a state-of-the-art product revolutionizing data analytics and machine learning workspaces. Databricks are a complete solution when it comes to working with data.
I rate the overall product an eight out of ten.
An amazing data analytics platform!
What do you like best about the product?
The Databricks Lakehouse Platform's seamless integration of data lakes and data warehouses, which offers the best of both worlds for data analytics and processing, is its most useful feature. Users in a variety of jobs are empowered by the platform's strong and intuitive user interface, which also promotes collaboration and increases output. Its rich built-in analytics and machine learning capabilities allow for sophisticated modelling and complex data transformations for the extraction of insightful information. The platform's scalability guarantees effective management of complex data processing operations. And finally, its strong data security and governance features provide users confidence when handling sensitive data.
What do you dislike about the product?
One area for improvement with the Databricks Lakehouse Platform is the occasional challenge faced when troubleshooting certain issues, where enhanced support options or an expanded knowledge base would be beneficial.
What problems is the product solving and how is that benefiting you?
The Databricks Lakehouse Platform tackles the challenge of seamlessly integrating data lakes and data warehouses, allowing me to effortlessly manage and analyze vast amounts of data. It has been a game-changer, streamlining my workflows, boosting productivity, and enabling me to extract valuable insights from diverse data sources. With its scalability and built-in analytics capabilities, I can optimize data processing and unlock actionable intelligence with ease.
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