The use case for Databricks is that we use the clustering for high big data processing within the cluster.
Databricks Data Intelligence Platform
Databricks, Inc.External reviews
637 reviews
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Experiencing smooth performance and cost advantages over previous tools
What is our primary use case?
What is most valuable?
I think it is difficult to determine which feature of Databricks I enjoy the most since there are many valuable features.
What's valuable about Databricks to my organization is that it is more cost-effective and provides better performance than the current AWS tools and services they offer.
What needs improvement?
I am uncertain about specific improvements for Databricks.
It would be beneficial to make Databricks even more cost-effective.
For how long have I used the solution?
I have been using Databricks for two years.
What do I think about the stability of the solution?
My experience with Databricks has been smooth, and I haven't encountered any issues.
Databricks is definitely a very stable product and reliable.
How are customer service and support?
I have not used Databricks customer service or support.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Before Databricks, I used Batch processing, Fargate, and possibly Kubernetes.
I switched from my previous solutions because they were either too expensive or too difficult to configure.
Which other solutions did I evaluate?
I have considered other solutions besides Databricks, such as Snowflake, but we haven't explored it extensively yet.
We are still early in our Snowflake experience, so we don't know the pros and cons compared to Databricks.
What other advice do I have?
My deployment model for Databricks is limited as I'm not a heavy user.
I am not the person who purchased Databricks, but it was possibly acquired through the AWS Marketplace.
I may not have utilized Databricks machine learning capabilities.
My experience with the pricing and licensing model is that it remains relatively expensive. Though it's less expensive than AWS, we still need a more cost-effective solution.
I would rate Databricks overall a nine out of ten.
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Shared notebooks and scheduling enhance cost efficiency
What is our primary use case?
We work on three platforms. Databricks is hosted on Azure for us, so we work with ADFS, Azure Data Factory, and also the AWS Cloud. We work for some customers.
What is most valuable?
The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster. This reduces costs. The scheduling part is managed by Databricks itself, for example, when it is idle, it will automatically turn off. All these features are handled by Databricks, reducing costs. We do not need to schedule separately.
For example, on AWS EC2, we have to create a Lambda function or use System Manager templates to schedule EC2 and EMRs. Here, it is taken care of, saving significant resources.
Additionally, notebooks can be shared within the development team which saves effort. Developers can share their notebooks. Git and Azure DevOps integration on the Databricks side is also very helpful.
What needs improvement?
The API deployment and model deployment are not easy on the Databricks side. We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools. Moreover, the API deployment should be simplified for ease of deployment and consumption.
For how long have I used the solution?
I have been using Databricks for approximately two and a half to three years.
What do I think about the scalability of the solution?
We have not faced any shortages so far. The clusters are available on demand, thus we have not encountered any scalability issues.
How are customer service and support?
We mostly had limited data support required from Databricks. Whenever we did need support, within two or three days the problem was solved. I would rate them ten out of ten.
How would you rate customer service and support?
Positive
What about the implementation team?
We bought it as a service, which is why we never implemented it ourselves. We do not have any implementation team.
Which other solutions did I evaluate?
For companies focused solely on data transformation, transferring data between databases, and not tackling machine learning or deep learning problems, I recommend ADF. It would be sufficient and cost-saving compared to a full-fledged solution like Databricks. However, for data analytics and solving ETL problems, one should consider Databricks.
What other advice do I have?
I would rate it nine out of ten.
Helps to have a good data presence but needs to incorporate learning aspects
What is our primary use case?
The product has helped in data fabrication.
How has it helped my organization?
Databricks has helped us have a good presence in data.
What needs improvement?
The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice.
For how long have I used the solution?
I have been using the product for more than six months.
What do I think about the stability of the solution?
I rate Databricks' an eight out of ten.
What do I think about the scalability of the solution?
I rate the tool's scalability an eight out of ten.
How was the initial setup?
The transition to Databricks was smooth.
What's my experience with pricing, setup cost, and licensing?
Databricks' price is high.
What other advice do I have?
I rate the solution a nine out of ten.
Processes tremendous data easily
What is our primary use case?
Our primary use case is in our project; we are dealing with Duo Special Data, where we need a lot of computing resources. Here, the traditional warehouse cannot handle the amount of data we are using, and this is where Databricks comes into the picture.
What is most valuable?
The processing capacity is tremendous in the database. We are dealing with Azure as storage, so we have not faced any challenges. And also the connectors to different data sources. Moreover, it is not a language-dependent tool. Therefore, development also takes place faster. It is one of the best features of Databricks.
What needs improvement?
There is room for improvement in the documentation of processes and how it works. I was trying to get one of the certifications, so I saw an area of improvement there.
For how long have I used the solution?
I have been using Databricks for eight to nine months.
What do I think about the stability of the solution?
It is a stable product for us. We didn't see any challenges.
What do I think about the scalability of the solution?
There are around 30 to 35 users in our organization.
How was the initial setup?
The initial setup was easy because the third-party team made the clusters for us.
What about the implementation team?
A third-party team enabled the cluster to make the setup easy for us.
What other advice do I have?
I would advise using it based on the use case because it easily handles big data. It is your go-to tool if you are dealing with massive data.
Overall, I would rate the solution a nine out of ten. The tool performs well in various use cases, availability of documentation online, and compatibility with big data systems like GCP, Azure, or AWS.
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