We compared Snowflake and Firebolt based on our user's reviews across various parameters. After reading all of the collected data, you can find our conclusion below.
Both Snowflake and Firebolt receive high marks for performance, user-friendliness, and cost-effectiveness, attracting users with their data management solutions. Snowflake is praised for its powerful performance, scalability, and speedy query execution, coupled with a positive customer service experience and a straightforward licensing model. The platform’s ability to handle large workloads and manage numerous concurrent users efficiently stands out, as does its positive return on investment. Firebolt is recognized for its swifter deployment process, exceptional query speeds, and cost-efficiency, made possible by its elastic scalability and intuitive interface. While its documentation and pricing model clarity could be improved, Firebolt's competitive pricing and flexible licensing options are well-received, along with the commendable customer support. Despite their distinct advantages and minor areas for improvement, both platforms excel in enhancing data analytics and operational efficiency for their users.
The summary above is based on 76 interviews we conducted recently with Snowflake and Firebolt users. To access the review's full transcripts, download our report.
"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."
"The solution is stable."
"My company wanted to have all our data in one single place and this what we use Snowflake for. Snowflake also allows us to build connectors to different data sources."
"Its performance is a big advantage. When you run a query, its performance is very good. The inbound and outbound share features are also very useful for sharing a particular database. By using these features, you can allow others to access the Snowflake database and query it, which is another advantage of this solution. It has good security, and we can easily integrate it. We can connect it with multiple source systems."
"It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL."
"For us, the virtual warehousing is likely the most valuable aspect."
"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."
"The querying speed is fast."
"It is very fast and the performance is great."
"Firebolt's engine takes a long time to start because it needs to make engine calls."
"Support needs improvement, as it can take several days before you get some initial support."
"Snowflake can improve its machine learning and AI capabilities."
"The cost of the solution could be reduced."
"Currently, Snowflake doesn't support unstructured data."
"There is a need for improvements in the documentation, this would allow more people to switch over to this solution."
"The user interface continues to be an issue, especially when we need to get data out of Snowflake. It's very easy to get data in, but it's not too easy to get it out or extract it."
"The complexity of the initial setup of Snowflake depends on the use case. However, Snowflake itself, we don't set it up. The difficulty comes from the ingestion patterns, depending on what data I'm putting in, what kind of enrichment, and what additional value we have to add. However, it does tend to get complex because we have a lot of semi-structured data which we need to handle in Snowflake. There have been some challenges."
"Some SQL language functions could be included."
Firebolt is ranked 14th in Cloud Data Warehouse with 1 review while Snowflake is ranked 1st in Cloud Data Warehouse with 94 reviews. Firebolt is rated 9.0, while Snowflake is rated 8.4. The top reviewer of Firebolt writes "Can quickly query it to generate quick results". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Firebolt is most compared with Microsoft Azure Synapse Analytics, Yellowbrick Cloud Data Warehouse and Amazon Redshift, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and AWS Lake Formation.
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