Real-Time Analytical Database for
‍AI & Data Applications

Firebolt delivers complex, sub-second Postgres SQL queries for high concurrency workloads to support AI and customer facing data applications.

Engineered Price-Performance out of the box

Designed and optimised to ensure ultimate performance and efficiency.

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Indexes & Reuse

Innovative subresult-reuse and specialized indexes support the most complex and demanding AI and Data Applications at high load.

Efficient Run-Time

Firebolt’s configurable execution engine delivers millisecond response times over TB datasets, by leveraging query optimization, distributed processing, multi-threading, vectorized processing, tiered caching and resource aware scheduling and scaling.

State-of-the-Art Optimizer

Firebolt’s query optimizer dynamically refines SQL execution by analyzing data distribution, indexing, and historical query patterns—optimizing performance for complex joins, high-concurrency analytics, and AI-powered applications.

Unparalleled Price-Performance Ratio

For high-performance, high-concurrency analytics and AI applications

Indexes & accelerators

Optimize performance of analytics and AI applications with JOIN accelerators and specialized indexes, including support for vector search.

Efficient run-time

Firebolt’s execution engine optimizes query performance with distributed multi-threading, vectorized processing, tiered caching, and resource-aware scheduling—delivering sub-second response times for analytics and AI-driven applications.

State-of-the-art optimizer

Firebolt’s query optimizer dynamically refines SQL execution by analyzing data distribution, indexing, and historical query patterns—optimizing performance for complex joins, high-concurrency analytics, and AI-powered applications.

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Efficient Data Pipeline

Fast Ingestion

Onboard large datasets with schema inference and parallel ingestion. Supports Parquet, JSON, CSV, AVRO, ORC, and Iceberg.

Low -latency Updates & Deletes

Updates and deletes efficiently maintain indexes and aggregations, ensuring optimized AI applications and analytics workloads.

ACID Compliance

Enjoy relational database atomicity, consistency, isolation and durability with SQL simplicity.

Multi-stage Query Execution

Scale-out processing with distributed, point-to-point shuffle reduces network transfers while optimizing resource consumption.

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Power Mixed Analytics Workloads

The capabilities of a data warehouse with the speed of a query accelerator - all in one platform

Adaptive Workload Management

Firebolt dynamically optimizes workload execution, managing tasks from admission control to infrastructure scaling—balancing performance across analytics and AI-enabled applications.

Workload 
Isolation

Separate mission critical workloads with their own optimised compute resources, with no complex data duplication and it’s management.

Distributed Writes 
& Global Consistency

Decoupled and distributed metadata provides consistency with transactional writes from any compute resource, and enables zero-downtime, no workload interruption upgrades.

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Scale with Multidimensional Elasticity

Tune compute resources per workload for optimized performance and cost

Node type
Number of nodes
Select between 1-128 compute nodes.
Number of clusters
Add up to 10 clusters to increase query concurrency.
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Consumption per hour
8
FBU
Firebolt unit is a normalized measurement of consumption.

Instant and Online Elasticity

Firebolt instantly scales compute resources to match workload demands, ensuring optimal performance for both analytics and AI applications.

Support Dynamic Concurrency

Firebolt dynamically scales compute clusters to handle high-concurrency workloads, ensuring seamless execution of analytics queries and AI-powered applications.

Fine-Grained Scaling

Scale compute incrementally to reach the best price performance for analytics and AI applications.

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Develop Data Products Faster

Empower data engineers, developers, and DevOps engineers with tools for the entire data lifecycle—now with support for AI applications, delivering low-latency, high-performance data access.

Everything in SQL

Use SQL to build robust analytics solutions. Data model, security, infrastructure - all built on the SQL object model.

Collaborative Workspace

Increase productivity and code velocity with a simple, easy-to-use environment built for collaboration.

Standards-based APIs / SDKs

Develop Python, Node, Java, Go and .NET-based applications using Firebolt SDKs.

CI/CD ready

Simplify environment management for automated testing and deployment, accelerating development cycles.

Integrations

Integrate with your choice of data transformation, orchestration, observability, and visualization tools.

Develop
Configure
Govern
Python
JAVA
GO
Node
.Net

Secure and Govern your Data Assets

Democratize your data with the right controls

Safeguard your data assets with a multi-layered security approach, ensuring compliance across analytics and AI-powered applications with RBAC, SSO, and network policies.

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Streamline governance using organizations and accounts, ensuring efficient spend management and consumption control. This approach facilitates the oversight of data assets, enhancing both operational efficiency and cost-effectiveness.

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Cloud Data Analytics FAQs

Key Features for Real-Time Data Analytics in the Cloud

  • Scalability: Dynamically scale resources to meet growing data demands.
  • Speed: Execute complex queries in seconds, enabling real-time analytics.
  • Integration: Seamlessly connect with various data sources, including SaaS platforms and on-premises systems.
  • Security: Robust security features, including encryption and compliance with industry standards.
  • ‍Cost-Efficiency: Pay only for the storage and computing power you use.

Benefits of Real-Time Data Analytics in the Cloud

  • Enhanced Performance: Faster query execution compared to traditional systems.
  • Improved Accessibility: Access your data from anywhere with an internet connection.
  • Simplified Maintenance: Eliminate the need for hardware maintenance and upgrades.
  • Data Integration: Consolidate data from multiple sources for comprehensive insights.
  • ‍Cost Savings: Reduce capital expenses associated with on-premises infrastructure.

What is the difference between a cloud analytical database and an on-premises data warehouse?

A cloud analytical database is hosted on cloud servers and offers scalability, flexibility, and reduced maintenance. On-premises data warehouses require significant hardware investment and manual upkeep.

How secure is Firebolt’s cloud analytical database?

Cloud analytical databases use advanced security measures such as encryption, access controls, and compliance with standards like GDPR, HIPAA, and SOC 2.

Can I integrate a cloud analytical database with my existing systems?

Yes, most cloud databases offer seamless integration with various data sources, including ERP systems, CRM platforms, and third-party analytics tools.

How much does a cloud data warehouse cost?

Costs vary based on storage capacity and query usage. Contact us for a quote.

What industries benefit from using a cloud analytical database?

Industries such as finance, healthcare, retail, and technology benefit greatly by using cloud data warehouses for analytics, compliance, and customer insights.

Do I need technical expertise to use a cloud analytical database?

Not necessarily. Many cloud data warehouse solutions are designed with user-friendly interfaces and automated features to simplify data management.

Can I migrate data from an existing system to a cloud analytical database?

Yes, most cloud database providers offer migration tools and support to facilitate the transition.

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