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 an impressive tool for data migration and integration."
"The ease of use and its accessibility are valuable."
"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."
"It is a cost-effective solution."
"The solution is very simple and stable."
"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."
"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."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"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 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."
"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."
"We can centralize all our data models."
"It is a pretty stable solution because it is a cloud-based product."
"Databricks' technical support takes a while to respond and could be improved."
"Databricks could improve in some of its functionality."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"The integration features could be more interesting, more involved."
"In the next release, I would like to see more optimization features."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"Doesn't provide a lot of credits or trial options."
"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."
"The integration with different databases must be improved."
"Stability needs improvement."
"The product does not have documented material."
"Integrations with other BI tools could be better."
"The visualization capability of the product is limited."
"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."
"It needs to be more user-friendly."
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, Dremio and Microsoft Azure Machine Learning Studio, whereas Looker is most compared with Amazon QuickSight, Tableau, Google Data Studio, SAP BusinessObjects Business Intelligence Platform and Qlik Sense.
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