Learn about the different methods deployed in Firebolt for reducing the number of scanned rows (aka pruning).
Discover how Firebolt's primary index optimizes data handling for large-scale analytics, enhancing query performance.
This blog describes our thinking and guiding principles behind design choices while building Firebolt.
This blog is a GA announcement of Firebolt’s next-gen cloud data warehouse that delivers low-latency analytics at scale.
Deep dive into how Firebolt optimizes query performance through caching and reusing results of parts of the query plan.
Uncover Firebolt’s Engine internals featuring zero-downtime upgrades, multi-dimensional elasticity, and granular scaling
This guide will provide you with the fundamental knowledge necessary to handle semi-structured data effectively.
Technical deep dive on how Firebolt evolved into a PostgreSQL-compliant database system.
Read on to find out how Lurkit is using Firebolt over AWS to serve advanced gaming analytics
Scale one node at a time to adjust compute resources incrementally, ensuring an ideal price-performance ratio.
Firebolt Inc., a cloud data warehouse provider, announced its next-generation compute infrastructure, Engines.
One of the more common and costly mistakes in the many data implementations is confusion about keys.
An issue many coming into the data warehouse world is difficulty with is managing time variance at scale and efficiency.