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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
91
Ranking in other categories
Cloud Data Warehouse (9th), Data Science Platforms (1st), Streaming Analytics (1st)
Looker
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
19
Ranking in other categories
Embedded BI (8th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 8.5%, up 6.1% compared to last year.
Looker, on the other hand, focuses on Embedded BI, holds 7.7% mindshare, down 9.9% since last year.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Databricks8.5%
Snowflake17.0%
Teradata8.8%
Other65.7%
Cloud Data Warehouse
Embedded BI Market Share Distribution
ProductMarket Share (%)
Looker7.7%
Tableau Enterprise23.9%
Qlik Sense11.2%
Other57.2%
Embedded BI
 

Featured Reviews

ShubhamSharma7 - PeerSpot reviewer
Capability to integrate diverse coding languages in a single notebook greatly enhances workflow
Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.
Anton Nenov - PeerSpot reviewer
A BI tool to analyze data from multiple sources with an easy initial setup phase
I can say many things about the parts that need to be improved in Looker. 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. Blending data from different sources is not something that can be done easily.

Quotes from Members

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

Pros

"The technical support is good."
"Databricks helps crunch petabytes of data in a very short period of time."
"The integration with Python and the notebooks really helps."
"The solution offers a free community version."
"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 has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."
"The most valuable feature is the ability to use SQL directly with 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."
"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."
"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."
"The product is easy to use."
"From a developer's perspective, the way the functionality's being handled is great."
"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."
 

Cons

"There is room for improvement in the documentation of processes and how it works."
"The tool should improve its integration with other products."
"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."
"The integration and query capabilities can be improved."
"The initial setup is difficult."
"I would like more integration with SQL for using data in different workspaces."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"I would like it if Databricks made it easier to set up a project."
"It needs to be more user-friendly."
"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."
"The product does not have documented material."
"Stability needs improvement."
"The integration with different databases must be improved."
"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."
 

Pricing and Cost Advice

"The pricing depends on the usage itself."
"We only pay for the Azure compute behind the solution."
"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."
"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 cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."
"The solution is based on a licensing model."
"The solution requires a subscription."
"Databricks' cost could be improved."
"It is cheap."
"It's not cheap, but it's not expensive for big companies."
"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."
"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
18%
Computer Software Company
9%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
13%
Computer Software Company
12%
Retailer
7%
Media Company
6%
 

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...
What do you like most about Looker?
With Looker, I have experienced benefits in terms of usability and shareability.
What is your experience regarding pricing and costs for Looker?
I do not have to make any payments to use the solution. In the beginning, Looker may work fine for its users. If advanced users who have experience with BI tools use Looker, then they may find it t...
What needs improvement with Looker?
The visualization capability of the product is limited. From an improvement perspective, the product should have more visualization capability. I can't clean data in Looker, and if I try to do it, ...
 

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, Google and others in Cloud Data Warehouse. Updated: October 2025.
873,085 professionals have used our research since 2012.