5 considerations when configuring a cluster in Starburst Galaxy

Starburst Galaxy, a Software as a Service (SaaS) platform, provides users with the ability to configure clusters tailored to specific workload needs through various execution modes, such as Standard, Fault Tolerant, and Accelerated, optimizing analytics processes. It integrates with over 50 data sources and supports an open data lakehouse architecture using Trino and Iceberg, enhancing data analytics, applications, and AI workloads. Key considerations for configuring clusters include cluster execution modes, sizing, autoscaling, auto suspend, and scheduling, allowing for flexible and efficient management of resources. Warp Speed mode is ideal for interactive analytics with significant data filtering, while Fault Tolerant Execution (FTE) mode suits complex and memory-intensive queries, although it may be slightly slower. Autoscaling adjusts the number of workers based on CPU utilization, and auto suspend conserves resources by shutting down idle clusters. Scheduling features allow clusters to run continuously during specified timeframes, optimizing costs and performance.