What challenges did AnalyticDB customer face before AI implementation?

Enterprises processing multimodal Clip data needed to handle complex pipelines across video, point clouds, radar, GPS, and control signals. Traditional solutions had complex configuration, low efficiency, inflexible resource scheduling, and difficult multimodal data management.

Source

Alibaba

AnalyticDB Ray enables fully managed Ray-based Data+AI with heterogeneous CPU/GPU scheduling (Qwen-VL fine-tuning case)

Use case typeData platform modernizationUpdated 1 day ago

AnalyticDB Ray is a fully managed Ray service on Alibaba Cloud AnalyticDB for MySQL that supports cloud-native Data+AI workloads with hybrid CPU/GPU resource scheduling. The article describes PB-level multimodal processing and distributed fine-tuning scenarios, including Qwen-VL multimodal model fine-tuning through LLamaFactory integrated into AnalyticDB Ray.

Organization: AnalyticDB customer
Industry: Tech & Comms
Location: China
Published: July 2026

Reported outcomes

+80%

GPU utilizationProductivity & throughput

1.8xoverall performance5 mstask scheduling latency4,000,000 tasks/daydaily task schedules80,000 tasks/secondpeak task scheduling throughput

Strategic outcomes

Cost efficiencyLower barrier to entry for Ray-based data and AI workloadsScale & capacityEnabled integrated Data+AI architecture for multimodal workloadsOther strategic outcomeSupported distributed fine-tuning of Qwen-VL multimodal models

Catalog median for productivity & throughput deployments: +45% across 225 reported metrics. Compare benchmarks →

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Use case focus

Showing 3 of 3

1Data platform modernization
2Multimodal analytics
3AI model training

Enterprises processing multimodal Clip data needed to handle complex pipelines across video, point clouds, radar, GPS, and control signals.
Traditional solutions had complex configuration, low efficiency, inflexible resource scheduling, and difficult multimodal data management.

Alibaba Cloud launched AnalyticDB Ray as a fully managed Ray service with one-click deployment, full-link observability, automatic elasticity, and fine-grained heterogeneous CPU/GPU scheduling.
The service integrates with AnalyticDB for MySQL, Ray Object Store, Lance, and LLamaFactory to support distributed multimodal processing and Qwen-VL fine-tuning.

Technologies

AnalyticDB for MySQL AnalyticDB Ray Ray Lance LLamaFactory Qwen-VL Object Storage Service (OSS)

The article reports overall performance improved by 1.8 times, GPU utilization exceeded 80%, scheduling latency reached 5 ms to 20 ms, and one customer scenario handled nearly 4 million task schedules per day with peaks near 80,000 per second.

Architecture

AnalyticDB Ray is described as a fully managed Ray service on AnalyticDB for MySQL with a cloud-native Data+AI architecture. It uses a unified CPU/GPU resource pool, a pipeline stream computing engine, Ray Object Store for intermediate data, adaptive scheduling based on job profiles, built-in high-performance video processing operators, and runtime fencing via separate conda environments. The service integrates with AnalyticDB lakehouse storage, Lance, and LLamaFactory for multimodal workloads and model fine-tuning.

Sources & evidence1

Groundedness: 5/5Type: Blog PostPublished: Jul 11, 2026Publisher: Alibaba CloudEvidence: VendorConfidence: Medium

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