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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 (6th), 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 (16th)
 

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Databricks is 9.3%, down from 18.5% compared to the previous year. The mindshare of Google Cloud Datalab is 1.6%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Databricks9.3%
Google Cloud Datalab1.6%
Other89.1%
Data Science Platforms
 

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.
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

"I work in the data science field and I found Databricks to be very useful."
"It's easy to increase performance as required."
"The ability to stream data and the windowing feature are valuable."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"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 most valuable feature is the ability to use SQL directly with Databricks."
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The APIs are valuable."
"For me, it has been a stable product."
"Google Cloud Datalab is very customizable."
"All of the features of this product are quite good."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
 

Cons

"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"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."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"Would be helpful to have additional licensing options."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"In the next release, I would like to see more optimization features."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"The interface should be more user-friendly."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"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."
"The product must be made more user-friendly."
"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."
 

Pricing and Cost Advice

"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."
"I would rate Databricks' pricing seven out of ten."
"There are different versions."
"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."
"Databricks' cost could be improved."
"The product pricing is moderate."
"We only pay for the Azure compute behind the solution."
"I rate the price of Databricks as eight out of ten."
"The product is cheap."
"The pricing is quite reasonable, and I would give it a rating of four out of ten."
"It is affordable for us because we have a limited number of users."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Manufacturing Company
9%
Computer Software Company
8%
Healthcare Company
6%
Financial Services Firm
25%
University
9%
Outsourcing Company
7%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business27
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: March 2026.
884,797 professionals have used our research since 2012.