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."When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"The initial setup phase of Databricks was good."
"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."
"I like cloud scalability and data access for any type of user."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"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."
"Looker allows you to generate the most optimal SQL queries in a DC through UI actions. We had signed a contract with Google Cloud to use BigQuery. That was the primary reason we adopted Looker. It works better with BigQuery than any other BI platform. We also like how this tool was developed. It was designed with an eye toward microservices architecture."
"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."
"We can centralize all our data models."
"With Looker, I have experienced benefits in terms of usability and shareability."
"From a developer's perspective, the way the functionality's being handled is great."
"The stability of Looker has been good since I have been using it. However, it depends on what components are being used."
"The product is easy to use."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"Databricks has a lack of debuggers, and it would be good to see more components."
"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."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"There is room for improvement in the documentation of processes and how it works."
"I would like more integration with SQL for using data in different workspaces."
"The integration with different databases must be improved."
"Stability needs improvement."
"The visualization capability of the product is limited."
"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."
"It needs to be more user-friendly."
"Integrations with other BI tools could be better."
"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."
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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