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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 Mindshare Distribution
ProductMindshare (%)
Databricks10.4%
Snowflake15.8%
Teradata8.0%
Other65.8%
Cloud Data Warehouse
Embedded BI Mindshare Distribution
ProductMindshare (%)
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

"The processing capacity is tremendous in the database."
"Databricks serves as a single platform for conducting the entire end-to-end lifecycle of machine learning models or AI ops."
"The tool helps with data processing and analytics with large-scale data or big data since it is associated with managing data at a large scale."
"There are good features for turning off clusters."
"The most valuable feature is the ability to use SQL directly with Databricks."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"The initial setup phase of Databricks was good."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"The product is easy to use."
"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."
"With Looker, I have experienced benefits in terms of usability and shareability."
"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 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."
 

Cons

"Pricing is one of the things that could be improved."
"There should be better integration with other platforms."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files. Standardization of file paths on the system could help, as engineers sometimes struggle."
"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."
"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."
"My experience with the pricing and licensing model is that it remains relatively expensive. Though it's less expensive than AWS, we still need a more cost-effective solution."
"As a data engineer, I see cluster failure in our Databricks user databases as a major issue."
"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 product does not have documented material."
"Integrations with other BI tools could be better."
"The visualization capability of the product is limited."
"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."
 

Pricing and Cost Advice

"The solution requires a subscription."
"The price of Databricks is reasonable compared to other solutions."
"Databricks' cost could be improved."
"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."
"Databricks are not costly when compared with other solutions' prices."
"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."
"There are different versions."
"I rate the price of Databricks as eight out of ten."
"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."
"It is cheap."
"I do not have to make any payments to use the solution."
"Looker is expensive and could be made better by reducing it."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
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.
884,192 professionals have used our research since 2012.