Firebolt has officially launched FireScale, a cutting-edge benchmark designed to simulate real-world analytics workloads. The latest benchmark results confirm Firebolt as a leader in cloud data warehouses (CDWs), outpacing competitors like Snowflake, Redshift, and BigQuery in delivering low latency, high concurrency, and the best price-performance for data-driven AI applications.

FireScale Benchmark Results: Firebolt Dominates

Firebolt ran 25 queries sourced from real user query patterns on 1TB of simulated web traffic data. To test concurrency, the team selected five key queries and generated 50,000 variations, running them randomly to measure queries per second (QPS) under high-load conditions. The results were game-changing:

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  • Firebolt outperforms Snowflake by 8x in price-performance, Redshift by 18x, and BigQuery by a staggering 90x.
  • Achieving Firebolt’s performance with Snowflake would cost 37.5 times more, while Redshift and BigQuery struggled to match Firebolt’s efficiency.
  • For the same cost, Firebolt delivers 5.5x QPS compared to Snowflake and 10x QPS compared to Redshift.
  • Firebolt achieves near-linear scaling with added clusters, maintaining low latency at just 120 milliseconds with a throughput of 2500 QPS.

The Future of AI-Powered Data Warehousing

Igor Stanko, Chief Product Officer at Firebolt, emphasized the importance of high-performance data processing for AI applications. “With the rise of AI agents and real-time data processing, businesses need sub-second query speeds at a massive scale and cost efficiency. These FireScale benchmark results leave no doubt—Firebolt is the fastest and most cost-effective CDW to power AI-driven applications.”

To enhance its flexibility and efficiency, Firebolt recently introduced a choice between storage-optimized and compute-optimized compute families. This update allows users to fine-tune resources and optimize cost-performance. Mosha Pasumansky, Chief Technology Officer at Firebolt, stated, “With the compute-optimized family, users can achieve similar performance at half the price for many workloads. At Firebolt, when our users win, we win too!”

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FAQs

1. How does FireScale differ from other analytics benchmarks?

FireScale is specifically designed to simulate real-world workloads with a focus on low latency and high concurrency, making it ideal for AI and data-intensive applications.

2. Can Firebolt handle large-scale enterprise AI workloads?

Absolutely! Firebolt’s near-linear scaling, ultra-low latency, and high QPS performance make it a top choice for enterprises building AI-driven applications.

3. How does Firebolt help optimize costs compared to competitors?

Firebolt’s compute-optimized family and efficient query execution deliver the same (or better) performance at a fraction of the cost compared to Snowflake, Redshift, and BigQuery.

With FireScale, Firebolt is setting a new industry standard—ensuring that businesses can leverage AI and analytics with unprecedented speed, scalability, and affordability.

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