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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
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 June 2026, in the Cloud Data Warehouse category, the mindshare of Databricks is 9.7%, up from 9.1% compared to the previous year. The mindshare of Firebolt is 2.2%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Databricks9.7%
Firebolt2.2%
Other88.1%
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 also user-friendly, providing customizable codes and models that allow people to experiment quickly."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood."
"It is a cost-effective solution."
"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."
"Databricks is a unified platform that provides features like streaming and batch processing so all the data scientists, analysts, and engineers can collaborate on a single platform and it has all the features you need, so you don't need to go for any other tool."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"It is fast, it's scalable, and it does the job it needs to do."
"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 integration of data could be a bit better."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"While Databricks is generally a robust solution, I have noticed a limitation with debugging in the Delta Live Table, which could be improved."
"Databricks is still having some stability issues."
"The pricing of Databricks could be cheaper."
"The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"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."
"Firebolt's engine takes a long time to start because it needs to make engine calls."
 

Pricing and Cost Advice

"Databricks' cost could be improved."
"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."
"Databricks are not costly when compared with other solutions' prices."
"The solution is based on a licensing model."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."
"The pricing depends on the usage itself."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
10%
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 Enterprise57
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: June 2026.
900,644 professionals have used our research since 2012.