107x faster than an open-source CPU database in GPU-accelerated SQL analytics.
AI-assisted data analysis and report generation help users explore datasets, summarize findings, and turn query results into business-ready outputs.
Unified external source management and guided migration setup help teams bring data into the platform with less manual configuration.
Storage and compute are separated so persistent data remains durable while CPU and GPU compute resources can be started or stopped based on workload needs.
The platform becomes usable across the business. The data team is released from ad-hoc extraction and support work to concentrate on governance and modeling, and utilization of data assets rises materially.
Performance insight moves from weeks to T+1 and, in many cases, to minutes. Dashboards stay connected to the latest data while preserving sub-second response times, removing the trade-off between freshness and responsiveness.
Backtest cycles compress from days to minutes. Elastic compute is billed on demand, reducing idle cost. Strategies and results are reproducible and easy to share, supporting iteration at scale.
A standardized migration wizard shortens the migration cycle and eases the toolchain transition. Separation of storage and compute, combined with on-demand billing, delivers a significant reduction in total cost.
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