We performed a comparison between Databricks and Zendesk based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"Automation with Databricks is very easy when using the API."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"The solution is very easy to use."
"The integration with Python and the notebooks really helps."
"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."
"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."
"One of the most valuable features is the ease of use. If you take the standalone product, it is so easy to use, but if you want a tailor-made Zendesk Guide, you can't do it yourself. However, you can use a template that already exists—they have a lot, and they're very cheap, around 300-400 euros—and use it on all your brands. It's a very easy product to use."
"I found the user experience with vendors on Zendesk to be straightforward, especially when it comes to understanding and searching for specific tickets. The search and navigation tools are easy to use, and I haven't encountered any issues with delays or communication gaps in ticket resolutions."
"It has good management, the ability to sign tickets based on content, the multi-channel support, the self service portal, the integration with Salesforce, the setup process, and the product features as we are currently using them."
"The product offers very good management. It has a great ability to assign tickets based on content."
"It's a very stable tool, very powerful."
"The initial setup is simple and straightforward."
"The feature to move over my customer experience team tickets for different specialists is very valuable for my team."
"It's very convenient to use."
"The initial setup is difficult."
"I would like more integration with SQL for using data in different workspaces."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"The integration of data could be a bit better."
"A lot of people are required to manage this solution."
"I would like it if Databricks adopted an interface more like R Studio. When I create a data frame or a table, R Studio provides a preview of the data. In R Studio, I can see that it created a table with so many columns or rows. Then I can click on it and open a preview of that data."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"Pricing is one of the things that could be improved."
"Sometimes if there was a way to just flag the actual issue out of those email chains - that would be really helpful."
"The solution itself wasn't easy to set up."
"The solution could integrate better with QR codes from some websites such as Facebook."
"The price of the solution should be reduced."
"They have something called Zendesk Explore, which isn't as good as what they had in place previously."
"The support team is time-consuming, and they don't find the answer to our problem."
"If I write an article, and I have a team of 30 people, and they all have a Zendesk account, when I write an article, I send them an email. "Hey guys, I just wrote this article. It's one of the most popular topics this month on which we are not covered. Please check it and make sure that you include it in your resolutions". The issue is, once I send it to those 30 people, and they open it, the next morning, that article is the most popular article."
"The dashboard could be better."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Zendesk is ranked 4th in CRM Customer Engagement Centers with 57 reviews. Databricks is rated 8.2, while Zendesk is rated 8.2. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of Zendesk writes "Straightforward, very transparent, and very well organized". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas Zendesk is most compared with ServiceNow, JIRA Service Management, Atlassian Confluence, Freshservice and Microsoft Dynamics CRM.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
