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Databricks vs Firebolt 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
Ranking in Cloud Data Warehouse
4th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
93
Ranking in other categories
Data Science Platforms (1st), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)
Firebolt
Ranking in Cloud Data Warehouse
17th
Average Rating
9.0
Reviews Sentiment
7.9
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2026, in the Cloud Data Warehouse category, the mindshare of Databricks is 10.2%, up from 9.0% compared to the previous year. The mindshare of Firebolt is 1.9%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Databricks10.2%
Firebolt1.9%
Other87.9%
Cloud Data Warehouse
 

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.
Iqbal Hossain Raju - PeerSpot reviewer
Junior Software Engineer at a healthcare company with 10,001+ employees
Can quickly query it to generate quick results
We have used Snowflake before. We support both. Firebolt has better performance, executing queries much quicker than Snowflake. However, Snowflake has more functionality. Depending on the client's needs, we can recommend the best option. Firebolt is a relatively new technology. Snowflake has many functionalities. Firebolt does not support unloading data to S3. There is no built-in way to do this in Firebolt. Alternatively, the data can be retrieved using API calls and loaded to S3 manually. Data can be unloaded to S3 directly using Snowflake. Firebolt significantly improves our performance over Snowflake because it takes less time to execute queries. This is especially important for our company because we use some KPIs that require fast loading times.

Quotes from Members

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

Pros

"Databricks is a scalable solution. It is the largest advantage of the solution."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job, so you can create a robust solution by working together with other professionals."
"The most valuable feature is the ability to use SQL directly with Databricks."
"Databricks' capability to process data in parallel enhances data processing speed."
"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."
"The initial setup phase of Databricks was good."
"One of the newest features brought into this solution provides you with a way to solve, deploy, and train models using the platform itself, or it can connect to your Azure Machine Learning in order to train, deploy, and productionalize some of the machine learning models."
"There are good features for turning off clusters."
"Firebolt is fast for analytical purposes. For example, we have analytical data in our data warehouse, and Firebolt can quickly query it to generate quick results."
 

Cons

"The Databricks cluster can be improved."
"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."
"Overall it's a good product, however, it might get challenged over time with individual best-of-breed products."
"Costs can quickly add up if you don't plan for it."
"Pricing is one of the things that could be improved. Also, there could be improvement in the visual analytics space there and on the machine learning functions."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"The biggest problem associated with the product is that it is quite pricey."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"Firebolt's engine takes a long time to start because it needs to make engine calls."
 

Pricing and Cost Advice

"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"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."
"The solution requires a subscription."
"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."
"The price is okay. It's competitive."
"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 are not costly when compared with other solutions' prices."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
7%
Healthcare Company
5%
No data available
 

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...
Ask a question
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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
Information Not Available
Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse. Updated: May 2026.
893,164 professionals have used our research since 2012.