Try our new research platform with insights from 80,000+ expert users

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
7.2
Number of Reviews
41
Ranking in other categories
Web Analytics (2nd)
 

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of Firebolt is 0.8%, up from 0.4% compared to the previous year. The mindshare of Snowflake Analytics is 1.1%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Snowflake Analytics1.1%
Firebolt0.8%
Other98.1%
Cloud Data Warehouse
 

Featured Reviews

Iqbal Hossain Raju - PeerSpot reviewer
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
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."
"Its structure aids in storing, managing, and analyzing large datasets in the cloud, using various relationships like one-to-one and many-to-one, ensuring consistency in the data structure."
"The platform not only provides ease of use but also stands out for its speedy execution, conveying a sense of robustness and reliability that I find appealing."
"One of the distinctive features of Snowflake is its ability to handle large datasets efficiently."
"It is an all-in-one platform that provides the capabilities needed for various analytics tasks, including data warehousing for machine learning."
"The most valuable feature of Snowflake Analytics is its performance."
"I am impressed with the product's data-sharing feature."
"One of the key advancements in Snowflake Analytics is data sharing."
"The performance has been good."
 

Cons

"Firebolt's engine takes a long time to start because it needs to make engine calls."
"One area that could benefit from enhancement is the user interface for more visual ESM features."
"However, if it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it would be even better."
"End-to-end execution of jobs isn't possible with Snowflake, which means we have to do some customization."
"Snowflake could improve in the areas of advanced machine learning AML and generative AI."
"The solution needs to consider including some updates in the future."
"Navigating the user console can be challenging, particularly when looking for details like the account ID."
"The technical support is not very good."
"Machine learning should be improved."
 

Pricing and Cost Advice

Information not available
"The cost of Snowflake Analytics is low, any small organization can use it."
"Snowflake Analytics is a little more costly than Azure."
"The product's pricing is subjective."
"I rate the product price a seven on a scale of one to ten, where one is low price, and ten is high price."
"The tool is quite expensive."
"The pricing is on the higher side."
"It is an expensive solution, but the kind of usability and flexibility it proactively provides for the organizations justify the price."
"I have been using free trial version."
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
868,759 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
No data available
Computer Software Company
16%
Retailer
9%
Financial Services Firm
9%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise12
Large Enterprise21
 

Questions from the Community

What do you like most about Firebolt?
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.
What needs improvement with Firebolt?
Firebolt's engine takes a long time to start because it needs to make engine calls. Currently, the data size of Firebolt is small. It can be increased.
What advice do you have for others considering Firebolt?
One way to retrieve data from firewalls is to add query parameters to the connection string. For example, you can use the REST API to retrieve the security query. Some firewalls have been deployed ...
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?
There are some minor issues encountered with Snowflake Analytics, such as problems when working with identity or row number generating different results or issues with referential integrity, which ...
 

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, Google and others in Cloud Data Warehouse. Updated: August 2025.
868,759 professionals have used our research since 2012.