Databricks Reviews

Our primary use case is to decrease costs and prevent any security press on data. I'm an IT manager and we are customers of Databricks. 

I think what I value is more about the technology itself because you don't need to have too much knowledge to be able to use the solution. 

I think we are using a lot of people to manage this solution. I'd like to see the people using this solution sharing their knowledge. 

We've been using this solution for around two years. 

The stability is okay now although a month after the data load there was a limitation for the first time on the project. That sorted itself out. 

It's a scalable solution. 

We have a good connection with technical support. 

I think the point is that because we'll be working collaboratively in the future, internally and externally, we should compare experiences and exchange knowledge. 

I would rate this solution an eight out of 10. 

Our primary use case of Databricks is for advanced analytics. I'm the chief research officer of the company and we're customers of Databricks.  

I think the features I like the most are the scalability of the solution as well as its ability to share. We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.

I'd like to see more licensing options for the solution, the availability of additional pricing tiers. I understand it's not easy to achieve because it's a kind of platform-as-a-service type of solution. If you wanted to be more specific about the parts, and what you might or might not need, then you could save some money, and go for a lower level. Of course, that would then mean you'd have to manage more configurations which, as a user, would make things more complex but it would be good to have that option. The pricing is not the cheapest but it's understandable because it's a very high-end solution and easy to use, there's a lot of complexity masked away.

I would like to see additional monitoring tools and, in general, anything that can improve visualization of data. I know it's not the main point of Databricks and there are other tools that can be used, but anything that facilitates the integration of Databricks with visualization tools could be really useful. Increasing data scalability would also be great. 

I've been using this solution for a year. 

The solution has been very stable. 

Scalability of the solution seems very easy to achieve. 

We haven't had contact with technical support. 

The initial set was very straightforward because it's also in our Azure cloud so it was quite easy to set up and configure. Very intuitive.

I would rate this solution an eight out of 10. 

We use the solution for business engineering.

The solution is very simple and stable.

The tool should improve its integration with other products.

I have been using the solution for around two years.

I would rate the product’s stability a seven out of ten.

I would rate the tool’s scalability a seven out of ten.

The solution is very easy to setup. I would rate its setup a ten out of ten.

I would rate the tool’s pricing an eight out of ten.

The tool’s performance is great. I would rate it an eight out of ten.

I am using Databricks for creating business intelligence solutions.

The most valuable feature of Databricks is the integration with Microsoft Azure.

Databricks can improve by making the documentation better.

I have been using Databricks for approximately one year.

Databricks is stable.

The scalability of Databricks is good.

We have approximately 500 users using this solution in my organization.

I have not used the support from Databricks.

We previously used Microsoft stacks. We chose Databricks because the processing power was better and it was a better fit for our use case.

The initial setup of Databricks was not straightforward. We had to do trial and error and we learned as we went along.

I rate the initial setup of Databricks a four out of five.

We did the implementation of Databricks in-house. The solution requires ongoing maintenance.

I would recommend this solution to others.

My advice to others is for them to first do a small proof of concept and then see how it works out and then take it from there.

I rate Databricks an eight out of ten.

I use this for database machine learning, to construct different models for supermarkets, drug store management, and market involvement to identify business opportunities for clients.

We provide different statistical models and use different algorithms depending on the client.

I was a Lead Data Scientist in different companies. I implement data and build and optimize processes using machine learning techniques, aided by science and advanced analytics.

Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client.

There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable.

It's stable.

It's scalable.

I would rate technical support 4 out of 5.

Setup isn't difficult. We used about 15 people for deployment and maintenance. We have data scientists and statisticians using this solution and doing different analyses.

I would rate this solution 9 out of 10.

My advice is to use the different high analytics methodology, plan for the project, and recognize the different activities for the design.

We use Databricks for experimentation. For example, we do ML model building and training that is connecting to our data which resides in Azure. It offers very good integration with Azure. We've deployed some of our model inference tools in Databricks.

 Databricks integrates well with other solutions.

Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage.

Along with having connections to different databases for Git tools, adding libraries for easy access would be a benefit. As data scientists, we connect to different databases and different sources of data, having a library would be useful.

I have been using Databricks for approximately one year.

The solution is stable. We did not face any downtime.

Databricks is scalable. It operates three times faster than any of the other ecosystems which we have experimented on.

We have approximately five data scientists using this solution in my organization. We are a small company and as we grow, all our data scientists would be using this platform. We plan to increase usage.

The technical support is good. We didn't need a lot of support. There were a few times we needed some help on how to do certain operations.

The installation was straightforward because it is on the cloud. The full deployment took approximately one week.

We did the implementation of Databricks in-house. It only requires one person for the maintenance of the solution.

My advice to others wanting to implement this solution is to use a cloud environment. For example, we are using Azure with Databricks. It is much better than doing an on-premise implementation.

I rate Databricks an eight out of ten.

My company is a customer of Databricks. We use Data Science products for machine learning, engineering, and data preparation.

We have between five and eight people working on coding in Databricks. Indirectly, we have 1500 people consuming the data. We have plans to increase the usage of data bricks by 30% next year.

The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes.

Databricks does not always have clear updates. Often we find an update in the tool but we are not really sure what has changed. We would appreciate better communication from Databricks. It could be in the form of a friendly warning that talks about the updates. 

There would also be benefits if more options were available for workers, or the clusters of the two points.

I have been using Databricks for two years.

Databricks is stable, however, we do find some errors and don't understand what has happened. Usually, they are resolved within a few minutes. I would say it is 95% stable.

Scalability is really good.

I have not had to contact Databrick's support other than through the deployment, which they helped a lot. 

The initial setup of Databricks is straightforward and simple. It is not complex because they provide a lot of documentation. The deployment was fast, it took less than three days with five people assigned to the task.

We implemented in-house. It is difficult to find a good consultant or reseller for Databricks in Brazil.

We pay monthly on a pay as you go plan.

With Databricks, you may have a lot of devices. It is important to use each cluster for each kind of process and then not use the small clusters. Using the bigger cluster you will receive better performance and the use is closer and will save you money. 

It is important to code it in parts because if you code it all in full you could find some problems with performance.

I would rate Databricks a 9 out of 10.

I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job. So you can create a robust solution by working together with other professionals.

One area for improvement would be that anyone who doesn't know SQL may find the product difficult to work with. It would also be useful to have a remote support team inside Databricks, which would collect and analyze user feedback.

I have been using Databricks since 2018.

I had a little trouble with customer support but this was solved.

The initial setup was a little complex because it was a new architecture for the customer, so there was nothing to compare it to in order to accelerate the project. This meant the deployment of the first project using Databricks took almost nine months and the second took almost a year.