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 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."
"The solution is very easy to use."
"We have the ability to scale, collaborate and do machine learning."
"I work in the data science field and I found Databricks to be very useful."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"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."
"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."
"The ability to stream data and the windowing feature are valuable."
"It's a very stable tool, very powerful."
"It is a scalable solution."
"The stability has been very good."
"The initial setup is simple and straightforward."
"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."
"What is cool about Zendesk Guide is how it works together with others Zendesk products. Especially with support and with the analytics. Put those together for a small or medium-sized company and it's a really powerful tool."
"It's very convenient to use."
"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."
"Databricks has a lack of debuggers, and it would be good to see more components."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"Would be helpful to have additional licensing options."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."
"The product cannot be integrated with a popular coding IDE."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"It needs to improve in terms of its flexibility, price, and installation."
"As per me, there arent much significant issues or areas for improvement with Zendesk, as my usage of it is limited. I appreciate its ability to organize tickets effectively based on tags, allowing me to easily gather and analyze customer feedback and requests."
"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."
"Zendesk Guide's customization could be improved. I would like it to be easier and maybe open-sourced, so that if you have a developer in your company, you can do it yourself. Right now, that isn't allowed, so you need to have it done via the integrator. Another improvement—this is nit-picking—is that it could be less easy to make changes. Some things are so easy that they sometimes look a little amateur-ish. Most of the templates are built-in so they can be used directly, so they are very simple."
"It wasn't easy to set up so we're only using a third of all of the features,"
"Sometimes if there was a way to just flag the actual issue out of those email chains - that would be really helpful."
"The solution could integrate better with QR codes from some websites such as Facebook."
"Zendesk Guide could be improved by allowing us to put our assets in one location. What happens now for each article, for example, is we have to upload the images for that article to that location, so the image reuse is still not something that they have perfected. If they could allow us to update all the images in one location, and then pull the image from there, it would be easier when working on Multibrand projects. There are no Multibrand updates available—we have to update each brand manually. For my company, I have come up with an API tool which allows me to push the content to multiple brands together, but if you don't have something like that, you have to manually do it."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Zendesk is ranked 5th 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.
