Databricks Reviews

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Tristan Bergh
Real User
Data Scientist at a consultancy with 10,001+ employees
Oct 27 2019

What is most valuable?

Immense ease in running very large scale analytics, with a convenient and slick UI. This saved us from having to tweak, tune, dive into deeper abstractions, get involved… more»

How has it helped my organization?

Databricks took care of all the underlying cluster management seamlessly. We could configure our clusters to run and deliver results without any delays due to hardware… more»

What needs improvement?

The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment. Perhaps a… more»

What's my experience with pricing, setup cost, and licensing?

Set up a cluster in your cloud of choice, but Databricks' service might also be very competitive as their pricing units will be built in. Licensing on site I would counsel… more»

Which solution did I use previously and why did I switch?

Previously I used Hive and Livy in Zeppelin on an in-house Hadoop installation. The queries constantly threw exceptions and timeouts and the necessary configuration… more»

What other advice do I have?

By investing in people skilled in data querying, Python coding, and even basic Data Science, a Databricks setup will reward the business. Once the Databricks data flows… more»

Which other solutions did I evaluate?

I evaluated Hortonworks, Livy, and Zeppelin. These were unsuitable due to the unavailability of sufficiently skilled personnel.
Abhijith Dattatreya
Consultant
Business Intelligence and Analytics Consultant at a tech services company with 201-500 employees
Dec 12 2019

What is most valuable?

The most valuable feature is the ability to switch loads between multiple clusters. Automation with Databricks is very easy when using the API. The ability to write code and SQL in the same interface is useful. It is easy to connect notebooks to a cluster. There are a large number of inbuilt functions that help to make things easier.

What needs improvement?

Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems. As it is now, we have to go into the driver logs to identify the error messages properly. There is not much information about Databricks available online, such as cost. Whenever we want to find the actual costing, we have… more»

What other advice do I have?

My advice for developers who are interested in working with this solution is to first go through the Spark architecture. I would rate this solution a nine out of ten.
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Alexandre Akrour
Real User
CEO at Inosense
Dec 05 2019

What is most valuable?

Valuable features would have to include the Notebook for piping some models and the future of executing the notebooks in parallel, in batches, which is also something that we use. And we use the Notebook on Spark with Python.

What needs improvement?

Improvements could include the pricing, the product is a little expensive, although I think comparable to other similar options. The integration features could be more interesting, more involved. For example, we use the Database Notebook, which is not as great as Jupyter Notebook, for providing a… more»

Which solution did I use previously and why did I switch?

We previously used the earlier version of Azure Machine Learning services and we decided to move over because over time it became more difficult to deploy. That was two years ago, but now with the new version, it's much easier to deploy Machine Learning.

What other advice do I have?

The product has improved and I'm sure this will continue in the next versions. We are completely satisfied with it, the ease of connecting to different sources of data or pocket files in the search. I think it could be very interesting for users looking for a framework to use Databricks. I would… more»
ShrikanthHebbar
Real User
Delivery Manager at Syniti
Jan 08 2020

What is most valuable?

I found that PySpark is the most useful tool. It uses in-memory calculation and when you want to run a model it does it very quickly. We used to use Python and when we migrated to PySpark the performance was much better.

What needs improvement?

It would be very helpful if Databricks could integrate with platforms in addition to Azure. Having an open-source version or having the option to get a trial version of Databricks would be very helpful. It would be very useful for beginners if there were tutorials and examples on how to write code… more»

Which solution did I use previously and why did I switch?

Before using Databricks, we were running our own cluster with a web server that executed our Python queries.

What other advice do I have?

I work in the data science field and I found Databricks to be very useful. If I want to run any models then I can code them in PySpark. If you are coming from a Python background then you can write code in PySpark and it runs quickly. This is a good solution in terms of performance. I would rate… more»
Real User
Machine Learning Engineer at a tech vendor with 51-200 employees
Dec 25 2019

What is most valuable?

The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient.

What needs improvement?

The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's… more»

Which solution did I use previously and why did I switch?

We didn't previously use a different solution, however, we built our own from scratch. This is the first unified platform that we've used.

What other advice do I have?

I'm a software development engineer. I'm working with the latest version. As long as the developers have an understanding of spark, and understanding technical tricks, it's very fast in terms of using the database. I'd rate the solution eight out of ten.
PankajGaikwad
Real User
Data Science Developer at a tech services company with 501-1,000 employees
Dec 12 2019

What is most valuable?

Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great. This solution has very good machine learning libraries built-in. The support for big data is good.

How has it helped my organization?

Prior to using Azure Databricks in the cloud, we had Databricks installed in clusters. Since our implementation, the performance has increased and our cost has been reduced.

What needs improvement?

Databricks should have more libraries for predictive analysis and machine learning. It should have more compatible and more advanced visualization and machine learning libraries. As it is now, I have to try a customer algorithm in order for… more»

What's my experience with pricing, setup cost, and licensing?

I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.

What other advice do I have?

Databricks has been good and I like it. However, it would be improved with the enhancement of the machine learning libraries, and with the inclusion of visualization libraries. I would rate this solution an eight out of ten.

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User Assessments By Topic About Databricks

Find out what your peers are saying about Databricks, Amazon, Microsoft and others in Data Science Platforms. Updated: December 2019.
389,722 professionals have used our research since 2012.

Databricks Questions

What is Databricks?

Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.

Also known as
Databricks Unified Analytics, Databricks Unified Analytics Platform
Databricks customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

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