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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

"Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood."
"Databricks is definitely a very stable product and reliable."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The initial setup is pretty easy."
"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."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"The most significant benefit Databricks has brought to my company is the Unity Catalog."
"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."
"We can centralize all our data models."
"It's quite effortless to navigate through various applications and review their updated data in real-time."
"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."
"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."
"It is a pretty stable solution because it is a cloud-based product."
 

Cons

"Databricks' technical support takes a while to respond and could be improved."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"Performance could be improved."
"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."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."
"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"Integrations with other BI tools could be better."
"The product does not have documented material."
"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 visualization capability of the product is limited."
"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

"Price-wise, I would rate Databricks a three out of five."
"The solution is a good value for batch processing and huge workloads."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."
"The billing of Databricks can be difficult and should improve."
"The price of Databricks is reasonable compared to other solutions."
"I rate the price of Databricks as eight out of ten."
"The cost is around $600,000 for 50 users."
"It's not cheap, but it's not expensive for big companies."
"It is cheap."
"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%
Manufacturing Company
9%
Computer Software Company
8%
Healthcare Company
6%
Financial Services Firm
13%
Retailer
9%
Computer Software Company
8%
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.
884,076 professionals have used our research since 2012.