Today, Firebolt announced its benchmark results on FireScale, a new benchmark simulating real-world workloads. Firebolt ran the FireScale benchmark on Firebolt as well as other cloud data warehouses (CDWs) such as Snowflake, Redshift and BigQuery. The results prove Firebolt to be a clear leader in CDWs in delivering low latency, high concurrency and the best price-performance for data-intensive AI applications.
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Firebolt FireScale Benchmark Results
In the benchmark, Firebolt ran 25 queries taken from real user query patterns on 1 TB of simulated web traffic data. For concurrent benchmarking, they selected 5 of those queries and generated 50,000 variations that were run in a random order, measuring queries per second (QPS) when 50+ simulated clients are submitting new queries as soon as they get results.
Here is a summary of the FireScale benchmark results:
- Firebolt is 8x better in price-performance than Snowflake, 18x better than Redshift and 90x better than BigQuery.
- To achieve Firebolt’s performance characteristics, Snowflake is 37.5 times more expensive, whereas Redshift and BigQuery failed to achieve anywhere close to similar performance numbers.
- For equivalently priced engines, Firebolt delivers 5.5x QPS compared to Snowflake and 10x QPS compared to Redshift. Firebolt also exhibits near-linear scaling when adding clusters, delivering low latency of 120 milliseconds with a throughput of 2500 QPS.
“At Firebolt, we are focused on building the next-generation cloud data warehouse for companies creating data-intensive AI applications,” said Igor Stanko, Chief Product Officer at Firebolt. “With the coming wave of AI agents and related applications, it has never been more important to be able to query and surface the right data with sub-second latency in a cost-efficient manner at a massive scale. These FireScale benchmark results prove conclusively that Firebolt is the fastest and most cost-efficient cloud data warehouse to help organizations build and deliver AI-powered applications and experiences for their customers.”
Firebolt recently introduced the ability to choose between storage-optimized and compute-optimized compute families, allowing users to fine tune compute resources to their workloads and have granular control over price-performance. “More choices for the users? Yes, please!” said Mosha Pasumansky, Chief Technology Officer at Firebolt. He added, “Compute-optimized family can deliver similar performance for half the price for many workloads. When our users win – we win too.”
To learn more about the compute family choices, please read our Under the hood of Firebolt compute families blog. For more details about the FireScale benchmark results, please read our launch blog. For an in-depth look at how we conducted the benchmark tests, please read our technical blog, and you can also run the FireScale benchmark yourself from this GitHub repo.
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About Firebolt
Firebolt is the cloud data warehouse for AI applications, built for speed, scale, and efficiency. With sub-second query performance, high concurrency, and multidimensional scaling, Firebolt empowers organizations to run AI-driven applications and low-latency analytics at unmatched speed—without the cost or complexity of legacy data warehouses. Whether structured, semi-structured, or unstructured, Firebolt turns any data into AI-powered insights faster than ever. For more information, visit www.firebolt.io and reach out to us on LinkedIn.
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