Engineered for millisecond query performance at lowest cost, driving data insights faster than ever
Firebolt announced the next-generation Cloud Data Warehouse (CDW) that delivers low latency analytics with drastic efficiency gains. Built across five years of relentless development, it reflects continuous feedback from users and real-world use cases. Data engineers can now deliver customer-facing analytics and data-intensive applications (data apps) more cost-effectively and with greater simplicity.
The Evolution of Firebolt
Firebolt is designed to meet the high demands of modern data workloads. Recognizing the need for a modern solution, Firebolt has reimagined how data should be stored, processed, and utilized, offering unmatched efficiency and low latency analytics. This engineering update marks a significant milestone in Firebolt’s mission to transform data warehousing.
“The data market is rapidly shifting from supporting internal analytics to enabling external data access and the creation of data-intensive products. This demands a modern cloud data warehouse that combines the ultra-low latency of top query accelerators with the ability to scale and transform massive, diverse datasets from any source, all while using standard SQL to handle any query complexity at scale — without compromise,” said Firebolt CEO & cofounder Eldad Farkash. “Years in the making, Firebolt comes from one of the best, most proven teams in the industry, listening closely to customers across mission-critical use cases, to deliver velocity, simplicity, and cost savings. This is a milestone in data warehousing, built for now and for the next generation of analytic applications.”
“Firebolt enabled us to achieve sub-second query performance across more than one petabyte of data in production while ingesting five terabytes daily, all without the need for extensive pre-processing,” said Yoav Shmaria, VP of R&D, Platform at Similarweb. “Firebolt’s architecture allows us to dynamically query massive datasets with high concurrency directly from raw data and effectively isolate workloads with decoupled storage and compute. This capability has been crucial in delivering complex analytics features at scale while maintaining predictable performance and reducing our total cost of ownership (TCO).”
Key Benefits of Firebolt
Organizations face the challenge of handling both internal analytics and external data applications, requiring them to manage separate systems that lead to increased complexity and total cost of ownership (TCO). Current solutions cannot deliver both the millisecond query responses and SQL capabilities needed at scale, forcing businesses to trade-off between speed and functionality.
Firebolt ends the struggle, redefining data analytics with a cost-effective unified platform that enables millisecond latency and high concurrency at scale to deliver powerful insights faster. Key benefits include:
- High Efficiency: Engineered for millisecond query performance at the lowest cost, delivering real-time insights to data apps without compromises.
- Concurrency at Scale: Supports high query per second (QPS) rates, ideal for applications requiring high performance under heavy load.
- Flexible Infrastructure: Fully decoupled and scalable architecture brings granular and multidimensional scaling to the right size compute resources for dynamic workload needs. Running diverse tasks and mixed workloads — such as data loading, ELT, and low-latency analytics — on isolated engines ensures predictable performance across all workloads while preserving transaction integrity and global consistency.
- SQL Simplicity: From provisioning to querying, everything in Firebolt is SQL. PostgreSQL-compliance enables integration with existing workflows and tools while offering support for both structured and semi-structured data analytics to meet diverse needs.
Customers Are Seeing Big Results
“Firebolt enabled us to analyze one million ad auctions per second, delivering a 400X speed improvement over MySQL and cutting storage costs by 77%. This level of performance allows us to provide real-time insights that are critical for optimizing mobile advertising strategies,” said Yaron Cohen-Leo, Business Intelligence Team Lead at Bigabid.
“Firebolt has completely transformed our data processing capabilities. Before, we struggled with slow query speeds and escalating costs with RDS/MySQL, which couldn’t handle our complex reporting requirements. Since moving to Firebolt, we’ve reduced our infrastructure expenses by 30% while achieving a 58X increase in query speed. Our customers now experience the fast, reliable performance they expect, and our team can deliver near real-time reporting by rapidly ingesting data from over 70 sources,” said Ryan McWilliams, CTO of VRIO.
“Firebolt’s indexing capabilities have transformed our data platform, delivering 60X faster query times and enabling us to create dealer-specific reports in just two minutes instead of over an hour. Firebolt’s scalability allows us to handle tables of well over a billion records efficiently, providing timely trend reports that are critical to our trading network. The configurability and decoupled compute and storage architecture enables us to manage workloads cost-effectively, while supporting our growth and allowing us to directly integrate beyond just reporting and into our daily workflows and end-user tools,” said Russell Guthrie, VP of Application Engineering for Dealer Trade Network (DTN).
“Firebolt is the only solution that allows us to run complex SQL queries over billions of records with high concurrency and low latency at the best price for performance. Its unique features are its low latency on complex SQL queries and great scalability — both in concurrency and in data volumes. Firebolt has enabled our team at Agritask to serve massive data at high concurrency directly to the Web UI,” said Andrew Schetinin, CTO of Agritask.
Firebolt’s leadership and team are well known for foundational contributions to hyperscalers’ CDW technologies, growing a data analytics unicorn, global technology awards, and their connection to TUM University database research expertise.
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Read our launch blog for more information.
