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Databricks vs Google Cloud Datalab comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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
Ranking in Data Science Platforms
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (9th), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)
Google Cloud Datalab
Ranking in Data Science Platforms
19th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (17th)
 

Mindshare comparison

As of February 2026, in the Data Science Platforms category, the mindshare of Databricks is 9.3%, down from 18.8% compared to the previous year. The mindshare of Google Cloud Datalab is 1.5%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Databricks9.3%
Google Cloud Datalab1.5%
Other89.2%
Data Science Platforms
 

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.
LJ
System Architect at UST Global España
dashboards are good and data visualization is more meaningful for the end-user
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcing your database with over a billion records, it can be tough for the end-user to manage the data. You need to have a single entity system in each environment. It's not because of GCP, but it would be great to have options like MongoDB or other similar tools in GCP. Then, we wouldn't always need to connect to the cloud and execute SQL queries. Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated. Once the data is collected, it should be easily sorted.

Quotes from Members

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

Pros

"Its lightweight and fast processing are valuable."
"The solution is very simple and stable."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"It's very simple to use Databricks Apache Spark."
"The solution is very easy to use."
"The solution offers a free community version."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"The ease of use and its accessibility are valuable."
"The APIs are valuable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"For me, it has been a stable product."
"All of the features of this product are quite good."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"Google Cloud Datalab is very customizable."
 

Cons

"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"However, the platform could become easier to use."
"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 could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"There should be better integration with other platforms."
"While Databricks is generally a robust solution, I have noticed a limitation with debugging in the Delta Live Table, which could be improved."
"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."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"The interface should be more user-friendly."
"The product must be made more user-friendly."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
 

Pricing and Cost Advice

"Price-wise, I would rate Databricks a three out of five."
"The pricing depends on the usage itself."
"The solution is based on a licensing model."
"I would rate the tool’s pricing an eight out of ten."
"The billing of Databricks can be difficult and should improve."
"The solution requires a subscription."
"The price of Databricks is reasonable compared to other solutions."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"It is affordable for us because we have a limited number of users."
"The product is cheap."
"The pricing is quite reasonable, and I would give it a rating of four out of ten."
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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
24%
Computer Software Company
10%
University
9%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business26
Midsize Enterprise12
Large Enterprise56
No data available
 

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 Google Cloud Datalab?
Google Cloud Datalab is very customizable.
What needs improvement with Google Cloud Datalab?
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcin...
What is your primary use case for Google Cloud Datalab?
It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten servers or systems. Some of them use a mobile network, some are ONTAP networks, and ...
 

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
Information Not Available
Find out what your peers are saying about Databricks vs. Google Cloud Datalab and other solutions. Updated: December 2025.
881,707 professionals have used our research since 2012.