We performed a comparison between Databricks and Looker based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The solution is very easy to use."
"We have the ability to scale, collaborate and do machine learning."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"The setup was straightforward."
"It's very simple to use Databricks Apache Spark."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"The product is easy to use."
"The stability of Looker has been good since I have been using it. However, it depends on what components are being used."
"I would rate the stability a ten out of ten. I didn't face any issues with stability."
"From a developer's perspective, the way the functionality's being handled is great."
"We can centralize all our data models."
"It is a pretty stable solution because it is a cloud-based product."
"With Looker, I have experienced benefits in terms of usability and shareability."
"It's quite effortless to navigate through various applications and review their updated data in real-time."
"I believe that this product could be improved by becoming more user-friendly."
"The pricing of Databricks could be cheaper."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"The integration features could be more interesting, more involved."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"Databricks has a lack of debuggers, and it would be good to see more components."
"In the next release, I would like to see more optimization features."
"It needs to be more user-friendly."
"The main area of concern in Looker is probably related to blending the data from the different sources, including the data present internally in the company and on the cloud."
"The product does not have documented material."
"Looker doesn't connect to Excel, which is a huge disappointment because a lot of data is presented in Excel. Also, it can't consume data directly from REST APIs, which is necessary. Looker needs to expand its horizons when it comes to data sources. The inability to connect to different data sources is hampering our use cases. Currently, it only has an ODBC connection that connects to a database. It needs to connect to other data sources, such as Excel, APIs, and different platforms."
"Stability needs improvement."
"Integrations with other BI tools could be better."
"The integration with different databases must be improved."
"The visualization capability of the product is limited."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Looker is ranked 5th in Embedded BI with 19 reviews. Databricks is rated 8.2, while Looker is rated 8.0. 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 Looker writes "The APIs are exposed at every level, so it's highly modular". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Dremio, whereas Looker is most compared with Amazon QuickSight, Tableau, Google Data Studio, SAP BusinessObjects Business Intelligence Platform and Qlik Sense.
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