Try our new research platform with insights from 80,000+ expert users

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
88
Ranking in other categories
Cloud Data Warehouse (7th), Data Science Platforms (1st), Streaming Analytics (1st)
Looker
Average Rating
8.0
Number of Reviews
19
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 7.2%, up 2.7% compared to last year.
Looker, on the other hand, focuses on Embedded BI, holds 9.1% mindshare, down 12.4% since last year.
Cloud Data Warehouse
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

"The setup is quite easy."
"It is fast, it's scalable, and it does the job it needs to do."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"Databricks' most valuable feature is the data transformation through PySpark."
"Automation with Databricks is very easy when using the API."
"It's great technology."
"Its lightweight and fast processing are valuable."
"The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster."
"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'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 product is easy to use."
"The stability of Looker has been good since I have been using it. However, it depends on what components are being used."
"It is a pretty stable solution because it is a cloud-based product."
"I would rate the stability a ten out of ten. I didn't face any issues with stability."
"We can centralize all our data models."
 

Cons

"Performance could be improved."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"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 product should provide more advanced features in future releases."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"The product does not have documented material."
"It needs to be more user-friendly."
"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 integration with different databases must be improved."
"The visualization capability of the product is limited."
"Stability needs improvement."
"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."
 

Pricing and Cost Advice

"The pricing depends on the usage itself."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"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 am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"We're charged on what the data throughput is and also what the compute time is."
"I would rate the tool’s pricing an eight out of ten."
"The price is okay. It's competitive."
"Databricks' cost could be improved."
"I do not have to make any payments to use the solution."
"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."
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
838,640 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
Educational Organization
38%
Computer Software Company
9%
Financial Services Firm
9%
Manufacturing Company
7%
 

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 ...
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: February 2025.
838,640 professionals have used our research since 2012.