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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
94
Ranking in other categories
Data Science Platforms (1st), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)
Firebolt
Ranking in Cloud Data Warehouse
18th
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 August 2026, in the Cloud Data Warehouse category, the mindshare of Databricks is 9.5%, up from 8.9% compared to the previous year. The mindshare of Firebolt is 2.2%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Databricks9.5%
Firebolt2.2%
Other88.3%
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

"It is a cost-effective solution."
"Databricks is also user-friendly, providing customizable codes and models that allow people to experiment quickly."
"Databricks' most valuable feature is the data transformation through PySpark."
"The technical support is good."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"You can spin up an Azure Databricks clustered, and integrating with it is seamless."
"Databricks helps crunch petabytes of data in a very short period of time for data scientists or business analysts, helping with fraud analysis, finance, projections, and more, which is exactly the purpose of big data and analytics."
"Data is open to everyone; they can access it through many channels, including notebooks or SQL."
"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

"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"In my opinion, areas of Databricks that have room for improvement involve the dashboards. Until recently, everyone used third-party systems such as Power BI to connect to Databricks for dashboards and reports, but they're now coming up with their IBI dashboard, and I think they're on the right track to improve that even further."
"I would like it if Databricks made it easier to set up a project."
"The first deployment is difficult. It is not straightforward and you have to think about a lot of stuff."
"I would like more integration with SQL for using data in different workspaces."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"Firebolt's engine takes a long time to start because it needs to make engine calls."
 

Pricing and Cost Advice

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"The price is okay. It's competitive."
"The billing of Databricks can be difficult and should improve."
"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."
"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 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."
"The solution is affordable."
"We're charged on what the data throughput is and also what the compute time is."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Manufacturing Company
10%
Computer Software Company
6%
Healthcare Company
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business26
Midsize Enterprise12
Large Enterprise58
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...
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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: July 2026.
908,800 professionals have used our research since 2012.