Starburst announced limited general availability of Starburst Torin, a GPU-native, Trino-based analytics engine for Starburst Enterprise. Built on NVIDIA cuDF, Torin accelerates SQL workloads with native GPU execution, delivering up to 7x faster query performance. By complementing Starburst’s existing CPU engine, Torin gives enterprises the flexibility to run workloads on CPUs or GPUs without changing existing Trino SQL queries, applications, or agents.
AI agents create a different kind of load on data platforms. A single agent task can trigger a chain of dependent queries, where delays in one query can slow the entire workflow. These bottlenecks also affect interactive analytics, making it harder to explore data, evaluate results, and make decisions in real time. Faster query execution helps agents complete analytical work sooner, improves user responsiveness, and lets teams run more workloads on available infrastructure.
Meanwhile, enterprises are investing in NVIDIA AI infrastructure to accelerate data processing for the agentic era. Torin extends those investments to SQL analytics without requiring a new data platform.
“Speed matters because of what it unlocks, which is why we built Starburst Torin. AI agents run dozens or hundreds of queries to finish a single task, so faster queries mean agents complete more work, teams run more workloads, and the business gets results sooner,” said Justin Borgman, Co-Founder and CEO at Starburst.
In Starburst benchmarks, Torin ran TPC-H queries up to 7x faster on NVIDIA Blackwell GPUs, with the fastest query running 11.4x faster. On ClickBench, an NVIDIA L4 GPU instance delivered 3.4x the throughput of the CPU baseline at a similar hourly hardware cost.
Torin is the result of close engineering work between Starburst and NVIDIA. Starburst built Torin’s SQL operators on NVIDIA cuDF, and NVIDIA engineers contributed cuDF expertise and guidance on optimizing for NVIDIA Blackwell GPUs. The results bring NVIDIA’s accelerated computing to the SQL teams already using Starburst. On the CPU side, Starburst Enterprise’s CPU engine also supports the NVIDIA Vera CPU, announced at GTC in March. For Starburst’s TPC-H benchmark at SF1000, Vera ran the queries 1.5x faster than a leading x86 CPU and used about 33 per cent fewer CPU seconds per query.
“Analytics and AI agents are putting more demand on data platforms, and accelerated data processing is how they keep up. By building Starburst Torin on NVIDIA cuDF, Starburst lets customers run their existing SQL on NVIDIA GPUs, without moving data, rebuilding workflows, or changing governance controls,” said Todd Mostak, Senior Director of Analytics and Data Intelligence at NVIDIA.
