We performed a comparison between Databricks and ThoughtSpot based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The processing capacity is tremendous in the database."
"The time travel feature is the solution's most valuable aspect."
"The solution offers a free community version."
"Databricks' most valuable feature is the data transformation through PySpark."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."
"It's easy to drill down or expand data to get more details right out of the box."
"It is easy to set up the solution."
"The initial setup was very straightforward."
"I would say the return on investment is good. Whatever we invested, we got results. We have been finding it easy to use and onboard new use cases."
"The ability to do ad hoc explorations of data has been most valuable."
"ThoughtSpot takes the modifying of existing reports out of our hands."
"I like ThoughtSpot's search capabilities. You can also create custom analytics even if you aren't an experienced data analyst. We have users with no data analytics experience making some of the dashboards we've created, copying components, and customizing them to their specific use cases."
"The scalability is good."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"The Databricks cluster can be improved."
"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"If I want to order columns, this feature is not there."
"ThoughtSpot is a fairly new product, so some usability aspects aren't as mature as we'd like them to be. One example is their organizational methodology, like how objects are organized in their dashboards inside the product. They're all on a flat list, which works if you've got five or 10 dashboards. However, it's insufficient when you're a large enterprise with multiple groups looking at the same dashboards. It isn't organized well."
"The dashboards could give you more ability to fine tune the appearance. You get a great deal more control over how something looks in Power BI than you do in ThoughtSpot."
"The one area of the solution that I do hear needs improvement is on the visualization front."
"In terms of features, I'd like to be able to pivot data - for example, going from rows to columns. It's not easy to do."
"A customized visualization is lacking in this product."
"I would like to see more flexibility in adding the pins. Currently, we have four different sizes in which I can add pins, but I would like to be able to resize my pins."
"The most difficult thing I found is that it only deals with the files and does not have direct connectivity to databases."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while ThoughtSpot is ranked 15th in BI (Business Intelligence) Tools with 8 reviews. Databricks is rated 8.2, while ThoughtSpot is rated 7.6. 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 ThoughtSpot writes "You can drill down into any data right out of the box, with a straightforward deployment, and great support". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio, whereas ThoughtSpot is most compared with Tableau, Microsoft Power BI, Looker, Amazon QuickSight and QlikView.
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.
