Try our new research platform with insights from 80,000+ expert users

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
92
Ranking in other categories
Cloud Data Warehouse (9th), 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 (9th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 10.0%, up 7.2% compared to last year.
Looker, on the other hand, focuses on Embedded BI, holds 6.4% mindshare, down 9.1% since last year.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Databricks10.0%
Snowflake15.9%
Teradata8.4%
Other65.7%
Cloud Data Warehouse
Embedded BI Market Share Distribution
ProductMarket Share (%)
Looker6.4%
Tableau Enterprise17.9%
Qlik Sense9.2%
Other66.5%
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

"Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood."
"It's very simple to use Databricks Apache Spark."
"Databricks serves as a single platform for conducting the entire end-to-end lifecycle of machine learning models or AI ops."
"The initial setup phase of Databricks was good."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"The fast data loading process and data storage capabilities are great."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"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."
"It's quite effortless to navigate through various applications and review their updated data in real-time."
"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."
"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 is a pretty stable solution because it is a cloud-based product."
"I would rate the stability a ten out of ten. I didn't face any issues with stability."
"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

"Cluster failure is one of the biggest weaknesses I notice in our Databricks."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"So far, we're not measuring any return on investment, such as saving time, money, or resources with Databricks."
"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."
"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"Databricks has a lack of debuggers, and it would be good to see more components."
"Integrations with other BI tools could be better."
"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."
"Stability needs improvement."
"The integration with different databases must be improved."
"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."
"The visualization capability of the product is limited."
 

Pricing and Cost Advice

"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."
"The billing of Databricks can be difficult and should improve."
"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."
"I rate the price of Databricks as eight out of ten."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."
"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"I do not have to make any payments to use the solution."
"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 is cheap."
"It's not cheap, but it's not expensive for big companies."
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
881,346 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
8%
Healthcare Company
6%
Financial Services Firm
14%
Computer Software Company
8%
Retailer
8%
Media Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business25
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
Earn 20 points
 

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: January 2026.
881,346 professionals have used our research since 2012.