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RUSEON Core vs Frigate NVR ​

Frigate NVR is a complete open-source NVR with real-time AI object detection (using Coral Edge TPU or OpenVINO). It is widely used in the home automation and self-hosted communities.

While Frigate is an application focused on AI detection and object tracking, RUSEON Core is a high-throughput video data infrastructure and ingest kernel.


1. Architectural Differences ​

1. CPU & Ingest Footprint (Zero-Transcoding vs FFmpeg) ​

  • Frigate NVR: Uses multiple FFmpeg processes per camera stream (detect stream, record stream, audio transcoding). Running 15–20 camera streams in Frigate can saturate 8–16 CPU cores due to software decoders and Python/C interop.
  • RUSEON Core: Uses Zero-Copy NALU Passthrough in pure Go. It extracts raw video frames without decoding pixels on the CPU. A single machine can ingest 600 simultaneous 30 FPS cameras (18,139 FPS, 1.34 Gbps total ingest) using under ~3.6 CPU cores on a 12-core server.

2. Storage Subsystem & Linux Page Cache ​

  • Frigate NVR: Relies on FFmpeg segmenting to write .mp4 chunks. Under heavy load or slow disk I/O, Python/FFmpeg processes can experience I/O wait bottlenecks and memory buildup in the Linux kernel cache.
  • RUSEON Core: Features native Fragmented MP4 (fMP4) recording integrated with sync_file_range and POSIX_FADV_DONTNEED. Flushes video chunks sequentially and instructs the kernel to drop video pages from RAM, keeping RSS memory strictly flat (~471 MB under 600 cameras).

3. Synergistic Integration: RUSEON + AI ​

RUSEON Core can serve as the high-performance video data infrastructure underneath AI engines:

  • RUSEON handles high-density RTSP ingestion, rock-solid 24/7 crash-proof recording, and WebRTC streaming.
  • Downstream AI workers (YOLOv11, Coral TPU, ONVIF analytics) connect to RUSEON via low-latency gRPC (FrameService.StreamFrames) or WebRTC DataChannels with zero CPU burn on the ingest node.

2. Comparison Summary Table ​

AspectRUSEON CoreFrigate NVR
ArchitectureHigh-Throughput Go Video EngineApplication-Level AI NVR
Transcoding OverheadZero (Raw NALU Passthrough)Moderate/High (FFmpeg decoders)
Max Streams per Node600+ Cameras (18,139 FPS / 1.34 Gbps)~10 – 25 Cameras
Page Cache ProtectionPOSIX_FADV_DONTNEED Built-inNone (OS Default)
Hardware Failure SafetyIsolated Lock-Free RingBufferProcess Restart / Buffer Queue
AI Metadata StreamgRPC & WebRTC DataChannelsMQTT / Internal Python DB

Released under the MIT License.