Optimize performance of any data model with JOIN accelerators and specialized indexes for efficient data pruning.
Combining distributed multi-threading, vectorized processing, tiered caching, sub-graph reuse, and resource-aware scheduling, Firebolt rapidly executes the query.
Firebolt's query optimizer turns any SQL into its most performant version by learning from the data profile and historical query patterns.
Onboard large datasets with schema inference and parallel loads. Supports popular file formats: Parquet, JSON, CSV, AVRO and ORC.
Updates and deletes are fast and efficient allowing you to keep your data, indexes and aggregations automatically refreshed.
Enjoy relational database atomicity, consistency, isolation and durability with SQL simplicity.
Scale-out processing with distributed, point-to-point shuffle reduces network transfers while optimizing resource consumption.
The capabilities of a data warehouse with the speed of a query accelerator - all in one platform
Firebolt automatically manages tasks from admission control to infrastructure scaling, supporting mixed workloads.
Separate sensitive workloads to run on their own compute resources, without copying data.
Decoupled metadata provides consistency with transactional writes from any compute resource.
Tune compute resources per workload for optimized performance and cost
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Allocate resources just-in-time to right-size your workloads.
Transparently add compute clusters to tackle the dynamic concurrency needs of your analytics-based applications.
Add nodes incrementally to reach the best price-performance balance.
Empower data engineers, developers and DevOps with tools for the entire data lifecycle
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Democratize your data with the right controls
Safeguard your data assets with a multi-layered security approach including network and infrastructure defenses, centralized authentication via single sign-on and multi-factor authentication, and fine-grained Role-Based Access Control (RBAC).
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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