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Databricks vs Looker comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Databricks
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (6th), Data Science Platforms (1st), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)
Looker
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
19
Ranking in other categories
Embedded BI (10th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 10.4%, up 7.7% compared to last year.
Looker, on the other hand, focuses on Embedded BI, holds 6.4% mindshare, down 9.0% since last year.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Databricks10.4%
Snowflake15.8%
Teradata8.0%
Other65.8%
Cloud Data Warehouse
Embedded BI Market Share Distribution
ProductMarket Share (%)
Looker6.4%
Tableau Enterprise17.6%
Qlik Sense8.6%
Other67.4%
Embedded BI
 

Featured Reviews

SimonRobinson - PeerSpot reviewer
Governance And Engagement Lead
Improved data governance has enabled sensitive data tracking but cost management still needs work
I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.
Kishore Jhunjhunwala - PeerSpot reviewer
Sr Analytics Consultant at a outsourcing company with 1,001-5,000 employees
A cloud solution for operational reporting but is expensive
Some basic feature that is available in other reporting tools is missing. Looker has the ability to show more than 5,000 rows for operational reporting. Some reporting tools allow users to scroll down to see more than 5,000 rows, but in Looker, you have to download the entire dataset. Looker should consider adding a scroll-down option to allow users to view large datasets on screen without downloading them. Looker has some options for granting users access as viewers. However, viewers cannot download the entire dataset. Only superusers can download the whole dataset on the Explore screen. This is a big limitation, as you cannot give any user viewer access. You can give access to superuser access, which is a cost to the company.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"I would rate them ten out of ten."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"It's easy to increase performance as required."
"The solution offers a free community version."
"Automation with Databricks is very easy when using the API."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"Databricks helps crunch petabytes of data in a very short period of time."
"The most valuable feature is the ability to use SQL directly with Databricks."
"We can centralize all our data models."
"From a developer's perspective, the way the functionality's being handled is great."
"It is a pretty stable solution because it is a cloud-based product."
"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."
"With Looker, I have experienced benefits in terms of usability and shareability."
"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."
 

Cons

"CI/CD needs additional leverage and support."
"I believe that this product could be improved by becoming more user-friendly."
"It's not easy to use, and they need a better UI."
"There has been a significant evolution in databases. One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files."
"The Databricks cluster can be improved."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"The API deployment and model deployment are not easy on the Databricks side."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"The product does not have documented material."
"Stability needs improvement."
"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 integration with different databases must be improved."
"It needs to be more user-friendly."
"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."
 

Pricing and Cost Advice

"There are different versions."
"The pricing depends on the usage itself."
"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"The solution is a good value for batch processing and huge workloads."
"The solution is affordable."
"Price-wise, I would rate Databricks a three out of five."
"It is cheap."
"Looker is expensive and could be made better by reducing it."
"The price of Looker usually depends on the solution's provider, but it is usually cheaper than the other products in the market. Looker is offered at different prices for different companies."
"It's not cheap, but it's not expensive for big companies."
"I do not have to make any payments to use the solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
8%
Healthcare Company
6%
Financial Services Firm
12%
Retailer
9%
Computer Software Company
9%
Media Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business27
Midsize Enterprise12
Large Enterprise56
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise8
Large Enterprise6
 

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
Ask a question
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Comparisons

 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
No data available
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Yahoo!, Etsy, Kohler, Hipcamp, Hubspot, Kickstarter, Venmo, Dollar Shave Club, 600+ customer
Find out what your peers are saying about Snowflake Computing, Microsoft, Teradata and others in Cloud Data Warehouse. Updated: February 2026.
883,448 professionals have used our research since 2012.