We performed a comparison between Databricks and Teradata Data Lab based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"We can scale the product."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"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 time travel feature is the solution's most valuable aspect."
"It's very simple to use Databricks Apache Spark."
"In the manufacturing industry, Databricks can be beneficial to use because of machine learning. It is useful for tasks, such as product analysis or predictive maintenance."
"The ease of use and its accessibility are valuable."
"In Data Lab, you can schedule any testing you want to do in production. You can take a small subset of data from production, copy it there, and run all your tests. It reduces your testing costs because it's all in the lab."
"It has increased the speed of reporting."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"The integration features could be more interesting, more involved."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"Can be improved by including drag-and-drop features."
"The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."
"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage."
"Their level of technical support is adequate. It could be better."
"The initial setup was complex as we had to rewrite a lot of the code."
"If I want to implement an upgrade, I'd like to see how it will be different. Ideally, Data Lab should help me test production items and also do future things. Future releases should be downloadable and testable in Data Lab."
Earn 20 points
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Teradata Data Lab is ranked 31st in BI (Business Intelligence) Tools. Databricks is rated 8.2, while Teradata Data Lab is rated 8.6. 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 Teradata Data Lab writes "You can schedule any testing you want to do in production". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas Teradata Data Lab is most compared with Teradata Vantage, Microsoft Power BI, Tableau and Oracle DataScience.com Platform.
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