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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 (7th)
 

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.
Kishore Jhunjhunwala - PeerSpot reviewer
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

"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"Databricks offers various courses that I can use, whether it's PySpark, Scala, or R."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"The simplicity of development is the most valuable feature."
"Easy to use and requires minimal coding and customizations."
"Its lightweight and fast processing are valuable."
"It's great technology."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"The stability of Looker has been good since I have been using it. However, it depends on what components are being used."
"The product is easy to use."
"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 is a pretty stable solution because it is a cloud-based product."
"With Looker, I have experienced benefits in terms of usability and shareability."
"We can centralize all our data models."
"It's quite effortless to navigate through various applications and review their updated data in real-time."
 

Cons

"I would like more integration with SQL for using data in different workspaces."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"The API deployment and model deployment are not easy on the Databricks side."
"Databricks has a lack of debuggers, and it would be good to see more components."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"The tool should improve its integration with other products."
"It needs to be more user-friendly."
"The visualization capability of the product is limited."
"Stability needs improvement."
"The product does not have documented material."
"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."
"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

"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."
"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."
"There are different versions."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"We only pay for the Azure compute behind the solution."
"I would rate Databricks' pricing seven out of ten."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"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."
"Looker is expensive and could be made better by reducing it."
"It is cheap."
"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%
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.
872,837 professionals have used our research since 2012.