Firebolt + Databricks: High Performance Analytics on Your Lakehouse

Sub-second analytics on the Databricks Data Intelligence Platform

Databricks powers your data transformation, governance, and AI workloads. Firebolt powers ultra-fast analytics serving and AI agent workloads. Together, Firebolt and Databricks deliver a modern lakehouse architecture that enables sub-second, high-concurrency analytics for embedded analytics, AI agents, and data-driven applications—without duplicating data or rebuilding pipelines.

Designed to accelerate your startup's growth

Built for the last mile of analytics

Databricks is optimized for large-scale data processing, transformation,and ML.

Firebolt complements Databricks by accelerating the final step: serving analytics to users and applications with ultra-low latency and high throughput.Ideal for customer-facing dashboards, embedded analytics, AI agent workloads and real-time APIs.

Query Databricks data directly

Firebolt integrates with Databricks Unity Catalog to query Iceberg tablesdirectly via REST API.

For Delta Lake tables, use Databricks UniForm to expose them as Iceberg format. Govern once in Databricks, serve everywhere with Firebolt—no data duplication required.

Scale without performance tradeoffs

Firebolt is purpose-built for high-concurrency analytics.

With smart caching, adaptive object storage reads, sub-result reuse, and multi-dimensional elasticity, Firebolt delivers predictable sub-second performance even with hundreds of concurrent users and thousands of queries per second.

Designed for fast, interactive analytics at scale

Customer-facing analytics dashboards and embedded analytics in SaaS applications
AI agent data access and RAG (retrieval-augmented generation) applications
High-QPS analytical APIs for real-time features
Interactive BI for large user populations
Real-time context retrieval for AI-powered applications

Architecture & Integration

Firebolt integrates seamlessly with Databricks using open table formats and shared metadata

Databricks manages data ingestion, transformation, and governance

Unity Catalog provides centralized metadata and access control

For Delta Lake tables, Databricks UniForm exposes them as Iceberg

Firebolt reads from the same object storage—no data duplication, no additional pipelines, no lock-in

This open architecture aligns with Databricks’ ecosystem approach and supports best-of-breed analytics stacks. 

Why data teams choose Firebolt

Sub-second query performance

At high throughput with predictable performance and cost at scale

Purpose-built serving layer

For external and embedded analytics

Built-in vector search

For AI-powered applications and semantic queries

Postgres-compatible SQL

Allowing existing queries to run without rewrites

Fully managed

Cloud-native architecture

Built on open standards

For flexibility and interoperability

Start serving analytics faster
Already using Databricks? Add Firebolt as a high-performance analytics layer on top of your lakehouse. Deploy in minutes and start delivering instant insights to users and applications—without re-architecting your data platform.
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