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Firebolt vs Snowflake comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 17, 2024

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
15th
Average Rating
9.0
Reviews Sentiment
7.1
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Snowflake
Ranking in Cloud Data Warehouse
1st
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
100
Ranking in other categories
Data Warehouse (1st), AI Synthetic Data (1st)
 

Mindshare comparison

As of June 2025, in the Cloud Data Warehouse category, the mindshare of Firebolt is 0.5%, up from 0.4% compared to the previous year. The mindshare of Snowflake is 18.9%, down from 23.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
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.
Snehasish Das - PeerSpot reviewer
Transformation in data querying speed with good migration capabilities
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses. One key feature is the separation of compute and storage, which eliminates storage limitations. It also has tools for migrating data from legacy databases like Oracle. Its stability and efficiency enhance performance greatly. Tools in the AI/ML marketplace are readily available without needing development.

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."
"Data Science capabilities are the most valuable feature."
"The product is quite fast."
"It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL."
"Everything is automatic, and I don't have to do any maintenance."
"Snowflake's most valuable features are data enrichment and flattening."
"The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
"It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud. It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it."
"Great scalability and near zero maintenance."
 

Cons

"Firebolt's engine takes a long time to start because it needs to make engine calls."
"The solution could use a little bit more UI."
"The data science functionality could be improved in terms of the machine learning process."
"The aspect of it that was more complicated was stored procedures. It does not support SQL language-based stored procedures. You have to write in JavaScript. If they supported SQL language and stored procedures, it would make migration from on-prem much simpler. In most cases, if an on-prem solution has stored procedures, they're usually written in SQL. They're not written as what most on-prem DBMS would refer to as an external stored procedure, which is what these feel like to most people because they're written in a language outside of SQL."
"There is room for improvement in Snowflake's integration with Python. We do a lot of SQL programming in Snowflake, but we go to a different tool to program when we have to in Python."
"From an improvement perspective, Snowflake can evolve in terms of writing costly, expensive queries with less cost and try to see if pipeline development can be made a little easier."
"I can only access Snowflake from the web. It would be better if we could have an app that we can install locally on our laptops to connect to the server without needing to go to the web page. Apart from that, it's hard to point out any limitations in the tool."
"There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was."
"I don't think that the AI tools in Snowflake are good."
 

Pricing and Cost Advice

Information not available
"It is pay-as-you-go. Its cost is in the medium range."
"We used Snowflake to see if it is cheaper than using BigQuery. It was just to maintain the cost or the KPI regarding the cost of connectivity by users. Snowflake wasn't cheaper than BigQuery, and its affordability was the main issue."
"It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive. Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way."
"The pricing part is based on the computing and storage. The costs are different and then there are services costs as well."
"The pricing for Snowflake is competitive."
"It's expensive."
"Users have to pay a licensing fee for the solution, which is expensive."
"Snowflake goes by credits. For a financial institution where you have 5,000 employees, monthly costs may run up to maybe $5,000 to $6,000. This is actually based on the usage. It is mostly the compute cost. Your computing cost is the variable that is actually based on your usage. It is pay-per-use. In a pay-per-use case, you won't be spending more than $6,000 to $7,000 a month. It is not more than that for a small or medium enterprise, and it may come down to $100K per year. Storage is very standard, which is $23 a terabyte. It is not much for any enterprise. If you have even 20 terabytes, you are not spending more than $400 per month, which may turn out to be $2,000 to $3,000 per annum."
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Top Industries

By visitors reading reviews
No data available
Educational Organization
24%
Financial Services Firm
16%
Computer Software Company
10%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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 do you like most about Snowflake?
The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power.
What is your experience regarding pricing and costs for Snowflake?
It is complicated to understand how requests impact warehouse size. Unlike competitors such as Microsoft and Databricks ( /products/databricks-reviews ), Snowflake lacks transparency in estimating ...
What needs improvement with Snowflake?
There is a need for a tool to help me estimate the cost of using Snowflake. Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently r...
 

Comparisons

No data available
 

Also Known As

No data available
Snowflake Computing
 

Overview

 

Sample Customers

Information Not Available
Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse. Updated: May 2025.
856,873 professionals have used our research since 2012.