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Firebolt vs Snowflake Analytics 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

Firebolt
Ranking in Cloud Data Warehouse
16th
Average Rating
9.0
Reviews Sentiment
7.1
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Snowflake Analytics
Ranking in Cloud Data Warehouse
10th
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
43
Ranking in other categories
Web Analytics (2nd)
 

Mindshare comparison

As of March 2026, in the Cloud Data Warehouse category, the mindshare of Firebolt is 1.7%, up from 0.4% compared to the previous year. The mindshare of Snowflake Analytics is 2.5%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Snowflake Analytics2.5%
Firebolt1.7%
Other95.8%
Cloud Data Warehouse
 

Featured Reviews

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.
Garima Goel - PeerSpot reviewer
Associate Principal Engineer at Nagarro
Have created secure cloud-based data lakes and improved real-time data processing using integrated AI features
There are many capabilities which Snowflake Analytics offers that I find valuable, such as the storage and compute engine that allows working with any cloud system such as AWS or Azure, alongside its efficiencies in storage computation and cost-effectiveness, which saves money compared to on-premise systems. We also have features such as pre-cached results, Time Travel, and fail-safe, which are very useful for restoring data if deleted accidentally, and the streams and data pipes that facilitate real-time ingestion are great features as well. Snowflake Analytics offers multiple new connectors, allowing me to connect it with Kafka, and with Snowpark, I can work with any programming language such as Python, Java, or Scala for data processing and analysis. The data sharing feature offered by Snowflake Analytics is good because it allows sharing specific sets of data to end customers or users from different Snowflake Analytics accounts without exposing the entire dataset for data security reasons. Snowflake Analytics' support for machine learning models and real-time insights has enhanced significantly. Originally, it wasn't strong in AI/ML, but now it has multiple models and forecasting capabilities, providing good competition to tools such as Databricks and Spark. In BI, I have worked majorly with Microsoft Power BI, and the integration with Snowflake Analytics is very easy. The way we integrate Snowflake Analytics with other on-premise systems just requires the warehouse details, username, passwords, and the account name, along with multiple options such as client ID and credentials for logging in and creating a session. The end-to-end encryption provided by Snowflake Analytics is very important because, in my previous firm, working in finance and investment management, data encryption is necessary due to the sensitive nature of customer data and the involvement of people's money. It's crucial to have encryption in transit and at rest, along with data masking features which Snowflake Analytics offers.

Quotes from Members

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

Pros

"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."
"It is an all-in-one platform that provides the capabilities needed for various analytics tasks, including data warehousing for machine learning."
"Features like the fact that the solution is very fast and available on the cloud are some of the valuable attributes of the solution."
"Deployment is straightforward as it's a SaaS product. No maintenance required."
"One of the distinctive features of Snowflake is its ability to handle large datasets efficiently."
"Considering everything I have accessed, the product's dashboard is good since it provides multiple good options, including customization options."
"One of the distinctive features of Snowflake is its ability to handle large datasets efficiently."
"The performance has been good."
"One advantage is that installation is unnecessary since it's cloud-based. You subscribe to a Snowflake instance, configure it, and start using it. It's very user-friendly and allows you to scale up or down based on usage."
 

Cons

"Firebolt's engine takes a long time to start because it needs to make engine calls."
"AIML-based SQL prompt and query generation could be an area for enhancement."
"We haven't seen any areas that are lacking."
"The tool should support EIM use cases. I guess the product is already working on it. I look forward to seeing inbuilt AI generative tools in the solution's future releases. The tool's price can be a little lower. The solution's on-premises support is also very limited. We have to rely on other support services to deploy it on-premises."
"The solution’s scalability could be improved."
"The distribution methodology isn't as strong as Bethesda or SAP HANA. It's not as strong as other competitors."
"The technical support is not very good."
"A room for improvement in Snowflake Analytics is Spark, particularly its connector for Spark. An additional feature I'd like to see in the next release of the solution is built-in analytics."
"Snowflake could improve in the areas of advanced machine learning AML and generative AI."
 

Pricing and Cost Advice

Information not available
"It's not costly if you configure it properly to ensure optimal performance. People don't configure it properly, which is why costs go up."
"Snowflake Analytics is a little more costly than Azure."
"I have been using free trial version."
"On a scale of one to ten, where one is a low price, and ten is a high price, I rate the pricing a seven. The solution's pricing is high."
"It is not overly expensive. I would rate the pricing a six out of ten, with ten being expensive."
"The tool is quite expensive."
"The product's pricing is subjective."
"When using Snowflake, you pay based on your usage. They calculate how much CPU has been used. If you use excess warehouse storage, you are charged one credit per hour. If you are in Asia, you are charged $3 per credit. If you have 10 users running parallel with the same excess, you will be charged $30."
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Top Industries

By visitors reading reviews
No data available
Computer Software Company
13%
Marketing Services Firm
9%
Financial Services Firm
7%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise13
Large Enterprise20
 

Questions from the Community

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What is your experience regarding pricing and costs for Snowflake Analytics?
Snowflake Analytics is quite economical. It does not appear to incur significant extra expenses beyond the solution's initial cost. However, a complete pricing analysis is still in progress.
What needs improvement with Snowflake Analytics?
In my opinion, Snowflake Analytics can be improved by introducing more features, such as additional integration options. I remember using Snowflake Pro, which allows exporting direct data into the ...
 

Overview

 

Sample Customers

Information Not Available
Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper
Find out what your peers are saying about Snowflake Computing, Microsoft, Teradata and others in Cloud Data Warehouse. Updated: February 2026.
884,797 professionals have used our research since 2012.