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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 (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

Satyam Wagh - PeerSpot reviewer
Consultant at Nice Software Solutions
Unified data workflows have cut ticket processing times and are driving faster business insights
Databricks already provides monthly updates and continuously works on delivering new features while enhancing existing ones. However, the platform could become easier to use. While instruction-led workshops are available, offering more free instructional workshops would allow a wider audience to access and learn about Databricks. Additionally, providing use cases would help beginners gain more knowledge and hands-on experience. Regarding my experience, I was initially unfamiliar with the platform and had to conduct research and learn through various videos. I did find some instruction-led classes, but several of those required payment. The platform should provide more free resources to enable a broader audience to access and learn about Databricks. The platform itself is user-friendly and easy to use without complex issues, so I believe it does not need improvement in its core functionality. Rather, supporting aspects can be enhanced.
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 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 helps integrate data science and machine learning capabilities."
"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."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."
"We can scale the product."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"It is a pretty stable solution because it is a cloud-based product."
"We can centralize all our data models."
"The stability of Looker has been good since I have been using it. However, it depends on what components are being used."
"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."
"I would rate the stability a ten out of ten. I didn't face any issues with stability."
"The product is easy to use."
 

Cons

"The biggest problem associated with the product is that it is quite pricey."
"The tool should improve its integration with other products."
"I think setting up the whole account for one person and giving access are areas that can be difficult to manage and should be made a little easier."
"Would be helpful to have additional licensing options."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"So far, we're not measuring any return on investment, such as saving time, money, or resources with Databricks."
"Databricks has a lack of debuggers, and it would be good to see more components."
"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 visualization capability of the product is limited."
"The integration with different databases must be improved."
"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."
"It needs to be more user-friendly."
"The product does not have documented material."
"Stability needs improvement."
"Integrations with other BI tools could be better."
 

Pricing and Cost Advice

"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"I would rate Databricks' pricing seven out of ten."
"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 cost is around $600,000 for 50 users."
"Databricks are not costly when compared with other solutions' prices."
"The product pricing is moderate."
"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."
"I do not have to make any payments to use the solution."
"Looker is expensive and could be made better by reducing it."
"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."
"It is cheap."
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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...
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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.
882,744 professionals have used our research since 2012.