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 most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"Databricks has helped us have a good presence in data."
"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"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."
"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."
"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."
"The ability to do ad hoc explorations of data has been most valuable."
"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 integration and query capabilities can be improved."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"Costs can quickly add up if you don't plan for it."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"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."
"Would be helpful to have additional licensing options."
"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."
"The one area of the solution that I do hear needs improvement is on the visualization front."
"A customized visualization is lacking in this product."
"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."
"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."
"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."
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.
