Databricks vs Looker comparison

The compared Databricks and Google solutions aren't in the same category. Databricks is ranked #7 in CDW , with an average rating of 8.3, and holds a 8.4% mindshare in the category. Google is ranked #5 in EBT , with an average rating of 8.0, and holds a 9.3% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

Databricks

Read 88 Databricks reviews

2,196 Views
1,662 Comparison Views

96% willing to recommend

Looker

Read 19 Looker reviews

1,537 Views
1,260 Comparison Views

80% willing to recommend

Databricks

Looker

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Executive Summary

We performed a comparison between Databricks and Looker based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: March 2025).

Buyer's Guide

Cloud Data Warehouse

March 2025

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Helped 844,944 peers since 2012

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

Ranking in other categories

Cloud Data Warehouse (7th), Data Science Platforms (1st), Streaming Analytics (1st)

Looker

Average Rating

8.0

Number of Reviews

Ranking in other categories

Embedded BI (5th)

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 8.4%, up 3.2% compared to last year.
Looker, on the other hand, focuses on Embedded BI, holds 9.3% mindshare, down 11.9% since last year.

Cloud Data Warehouse

Embedded BI

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

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.

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Kishore Jhunjhunwala

Sr Analytics Consultant at a tech vendor 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.

Read full review

Quotes from Members

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

Pros

"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."

"The solution is an impressive tool for data migration and integration."

"I would rate them ten out of ten."

"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."

"Ability to work collaboratively without having to worry about the infrastructure."

"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."

"Databricks' most valuable feature is the data transformation through PySpark."

"The solution offers a free community version."

More Databricks pros

"It is a pretty stable solution because it is a cloud-based product."

"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."

"We can centralize all our data models."

"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."

"The product is easy to use."

"From a developer's perspective, the way the functionality's being handled is great."

More Looker pros

Cons

"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."

"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."

"I have seen better user interfaces, so that is something that can be improved."

"There has been a significant evolution in databases. One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files."

"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."

"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."

"Databricks could improve in some of its functionality."

"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."

More Databricks cons

"Stability needs improvement."

"The product does not have documented material."

"It needs to be more user-friendly."

"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."

"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."

"The visualization capability of the product is limited."

Pricing and Cost Advice

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

"The solution is affordable."

"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 basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"The price is okay. It's competitive."

"It is an expensive tool. The licensing model is a pay-as-you-go one."

"The price of Databricks is reasonable compared to other solutions."

More Databricks pricing and cost advice

"I do not have to make any payments to use the solution."

"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."

"Looker is expensive and could be made better by reducing it."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Educational Organization

34%

Computer Software Company

10%

Financial Services Firm

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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 ...

See all answers

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...

See all answers

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...

See all answers

What do you like most about Looker?

With Looker, I have experienced benefits in terms of usability and shareability.

See all answers

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...

See all answers

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, ...

See all answers

Comparisons

Dataiku vs Databricks

Compared 11% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Dremio vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

Amazon QuickSight vs Looker

Compared 14% of the time

Tableau vs Looker

Compared 13% of the time

Microsoft Power BI vs Looker

Compared 9% of the time

SAP BusinessObjects Business Intelligence Platform vs Looker

Compared 8% of the time

Domo vs Looker

Compared 6% of the time

More Looker Competitors

Product Reports

Buyer's Guide

Databricks

March 2025

Download Databricks product report

Buyer's Guide

Looker

March 2025

Download Looker product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Databricks

Looker is a powerful data analytics platform that empowers businesses to explore and analyze their data in real time.

With its intuitive interface and robust features, Looker enables users to easily create and share interactive dashboards, reports, and visualizations.

The product's advanced data modeling capabilities and seamless integration with popular data sources make it a top choice for organizations looking to gain valuable insights from their data.

Google

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: March 2025.

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