Firebolt Analytics Inc
Firebolt builds a Postgres-compliant analytical database for engineers and AI agents, focused on sub-second analytics, high concurrency, and efficient execution at scale. Its architecture is intended to power data-intensive products and interactive analytics experiences rather than only traditional BI.
At a Glance
- Data engineering and software development teams
- AI application and agent builders
- Business intelligence vendors
- Cloud-native and big-data companies
- +2 more
AI Tools by Firebolt Analytics Inc
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Firebolt
Real Time Analytics Database
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Latest News
Firebolt open-sourced FuzzBerg for hunting bugs in Iceberg and file-format readers.
Firebolt published its ARM/Graviton rollout and benchmark results using customer workload replays and TPC-H.
Firebolt introduced Auror, an open-source Kubernetes admission webhook for efficient container-image verification.
Firebolt launched Firebolt Core, a free-forever self-hosted version of its distributed query engine.
Products & Services
A cloud-native, Postgres-compliant analytical database and data warehouse for sub-second SQL analytics, high concurrency, elastic scaling, and data-intensive applications.
Free-forever, self-hosted edition of Firebolt's distributed query engine. It can run from a laptop to on-premises or Kubernetes clusters and uses the same core engine as the managed service.
Model Context Protocol server that lets AI tools query Firebolt data, explore schemas, look up Firebolt documentation, generate SQL, and assist with client-code generation.
Open-source, high-performance Kubernetes admission webhook for validating container images, with caching and telemetry capabilities.
Market Position
Firebolt positions itself as an engineer-first alternative to Snowflake, Google BigQuery, Amazon Redshift, ClickHouse, and Databricks for interactive, low-latency analytics. Its differentiation is a purpose-built distributed engine, aggressive pruning/indexing, decoupled elastic compute and storage, Postgres compatibility, and a free self-hosted edition.
Leadership
Founders
Eldad Farkash
Firebolt co-founder and former CEO; previously co-founded Sisense and was part of its founding team.
Saar Bitner
Firebolt co-founder; previously a member of Sisense's founding team and served as Sisense's CMO and GM Israel.
Ariel Yaroshevich
Firebolt co-founder and former CTO; previously a member of Sisense's founding team.
Executive Team
Benjamin Wagner
CEO
Mosha Pasumansky
CTO
Previously a principal engineer on Google's BigQuery team.
Founding Story
The founders encountered the problem at Sisense: cloud data warehouses became increasingly expensive and struggled to deliver good performance for terabyte-scale analytics. They started Firebolt to rearchitect the warehouse around speed and efficiency, using compression, indexing, and a purpose-built query engine to support interactive data applications.
Business Model
Revenue Model
Usage-based managed database service: compute is billed per second, storage is pass-through object storage, and customers can choose managed service or bring-your-own-cloud deployment. Firebolt also uses a free-forever self-hosted Core edition to drive adoption while monetizing managed and enterprise deployments.
Pricing Tiers
Self-hosted edition; deploy on a laptop, on-premises infrastructure, or Kubernetes.
Choose region, node type, hardware profile, node count, and compressed data volume; includes $200 in free credits.
Run Firebolt using the customer's cloud environment; the public pricing page directs customers to configure an estimate or contact sales.
Target Markets
- Data engineering and software development teams
- AI application and agent builders
- Business intelligence vendors
- Cloud-native and big-data companies
- Customer-facing businesses serving real-time analytics
- Enterprises with large-scale analytical workloads
- Interactive analytics and customer-facing data applications
- AI-agent data layers and natural-language-to-SQL workflows
- Real-time and low-latency analytics at terabyte scale
- ELT, data transformation, and long-running asynchronous queries
- Business intelligence and self-service analytics
- Ad hoc analysis and production data workloads
- Lyft
- Credit Karma
- Nike
- Instacart