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."Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"Databricks integrates well with other solutions."
"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."
"I work in the data science field and I found Databricks to be very useful."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"With Looker, I have experienced benefits in terms of usability and shareability."
"It is a pretty stable solution because it is a cloud-based product."
"From a developer's perspective, the way the functionality's being handled is great."
"The product is easy to use."
"We can centralize all our data models."
"I would rate the stability a ten out of ten. I didn't face any issues with stability."
"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."
"The product cannot be integrated with a popular coding IDE."
"The Databricks cluster can be improved."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"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."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"A lot of people are required to manage this solution."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"The product does not have documented material."
"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."
"Stability needs improvement."
"The integration with different databases must be improved."
"Integrations with other BI tools could be better."
"The visualization capability of the product is limited."
"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."
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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