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."Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"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."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."
"It can send out large data amounts."
"The solution is very easy to use."
"With Looker, I have experienced benefits in terms of usability and shareability."
"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's quite effortless to navigate through various applications and review their updated data in real-time."
"It is a pretty stable solution because it is a cloud-based product."
"The product is easy to use."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"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."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"There should be better integration with other platforms."
"Databricks' technical support takes a while to respond and could be improved."
"The tool should improve its integration with other products."
"The integration and query capabilities can be improved."
"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."
"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 visualization capability of the product is limited."
"The integration with different databases must be improved."
"Stability needs improvement."
"It needs to be more user-friendly."
"The product does not have documented material."
"Integrations with other BI tools could be better."
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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