Built for production-grade Data and AI workloads, Firebolt gives engineers the performance, flexibility, and control they need.
Postgres compatible SQL, can run on Iceberg, and delivers strong price/performance even on complex high concurrency workloads.
Low-latency queries, complex joins, heavy batch ELT -all run efficiently in one place.
Firebolt is fast out of the box without requiring careful tuning. Our vectorized query engine scales up and out to give you the latency you need. Our query optimizer makes sure complex machine and AI generated queries have efficient query plans.
When running production workloads you need control and predictability. Firebolt lets you manage data layout, caching, query plans, and more. You also get rich observability to help you tune effectively.Decoupled metadata, storage, and compute lets you test changes in isolated environments without risking production.
Run it fully managed in the cloud or self‑host anywhere you wish. Either way you get the same efficiency, Iceberg support, and Postgres SQL compatibility.
“Firebolt immediately gave us faster performance at a much greater scale, which let our customers analyze huge datasets with sub-second performance. It also gave us the flexibility to deliver complex data features much faster.”
“Firebolt is a massive improvement to our BI efforts. Using the same test dataset of 100 million records, other databases took minutes, Firebolt analyzed in seconds.”
“Firebolt helped us with various scenarios leveraging REST APIs. I was really impressed by the speed. All this was done with minimal compute resources.”
“With Firebolt there’s a lower monthly cost and some very dramatic performance improvements. We’ve gone from minutes to seconds on particular sets of very tricky queries.”
“As a customer-facing product, we can’t have a 3-4 second delay when moving from a 6-month to a 12-month view. I need that instantly. And that’s what we get with Firebolt.”
“Whether we have 100, 200, or 250 users accessing a BI tool, we need consistent sub-second query performance. Firebolt is a key partner for us.”
Firebolt is built for performance: it has a mature planner, vectorized runtime, and fast shuffle. Fine grained control over data layout and indexing lets you run fast queries on terabytes of data. Shared computations are reused across queries.
Firebolt supports workload scaling by providing multidimensional elasticity. It allows you to independently and granularly scale compute resources up or down, in or out, and for concurrency, ensuring optimal performance and cost-effectiveness for your workload.
Read and write Iceberg tables. Firebolt supports file-based and REST catalogs. Queries on Iceberg run fast: our query planner, runtime, and storage are all optimized for it.
Postgres-compliant SQL extended for modern analytics: array processing with lambdas, schema inference, and vector search.
Firebolt has decoupled metadata, storage, and compute. All clusters can read and write the same data. Transactions are ACID, strongly consistent, and snapshot isolated. Multi statement transactions and RBAC allow you to build advanced, safe applications.
Scale to zero when you don’t need to run queries. New clusters are provisioned within seconds. Auto start and auto stop allow you to optimize cost. Clusters can be re-scaled without any downtime.
Scales out for multi-stage queries with fact:fact joins and high-cardinality aggregations. Data spilling for larger-than-memory processing.
Low latency, high concurrency at scale. Cross-query reuse. Resource aware admission control. Supports auto scaling.
Efficiently serve AI applications. Efficiently serve AI applications with fast vector search and flexible integration options. Use the MCP server or connect with tools like LangChain.