Tdarr

Project Overview

Tdarr is a cross-platform media library transcoding automation system for Windows, macOS, Linux, and Docker. It uses a distributed Server plus Node architecture: a central server schedules tasks while nodes on other devices execute them, turning idle hardware into a parallel processing fleet. A common use is batch converting H.264 video to H.265 (HEVC), saving 40%-50% of storage without visible quality loss. The app is driven through a web interface and works well alongside Sonarr and Radarr.

Item	Value
Platform	Windows, macOS, Linux, Docker
Engines	FFmpeg, HandBrake
Architecture	Server + distributed Nodes
Interface	Web UI

Turn idle machines into a transcode cluster and normalize your video library to space-saving formats.

Key Features

• Distributed transcoding: Server and Node are decoupled, letting multiple devices process one library in parallel
• CPU/GPU workers: transcode and health-check workers each come in CPU and GPU flavors, started and stopped as needed
• Plugin stacks: conditional plugins written in JavaScript, chained to clean up and standardize files
• Health checking: detects corrupt video files and repairs or remuxes them automatically
• Stream cleanup: batch removal of extra audio, subtitle, and metadata streams for better direct play
• Library analytics: search files by hundreds of properties; track size, codec distribution, and history
• 24/7 scheduling: per-library rules, filters, and schedules across a 7-day, 24-hour planner
• Folder watcher: monitored directories pick up new files automatically

Target Audience

• Users with large local media collections
• Media enthusiasts running NAS or home servers
• Users building libraries for Plex, Jellyfin, or Emby
• Tinkerers unifying video codecs and containers
• Owners of multiple idle PCs or GPUs

Quick Start

1. Download the server and node builds for your platform, or use the Docker image
2. Start Tdarr Server and open the web interface in a browser
3. Add local or remote nodes and allocate CPU/GPU workers
4. Add a library, then set transcode rules, plugin stacks, and schedules
5. Review scan results, start processing, and track jobs in the reports view

Core Advantages

• Space savings: H.264 to H.265 conversion typically reduces size by 40%-50%
• Horizontal scaling: old PCs and NAS boxes can join as nodes whenever available
• Programmable pipeline: plugin stacks with conditions can express almost any workflow
• Battle tested: officially tested against a dummy library of one million files

System Requirements

Item	Requirement
Server	Windows, macOS, Linux, or Docker
Node	Windows, Linux (incl. arm/arm64), macOS
GPU transcode	Intel QSV, NVIDIA NVENC, and similar hardware encoders
Companion tools	optionally pairs with Sonarr, Radarr, and similar

Notes

• Transcode time: a full first pass on a large library may take days; trial rules on a small subset first
• GPU setup: hardware transcoding needs proper drivers; enable the Nvidia runtime on unRAID or Ubuntu
• Keep originals: confirm original files are backed up before stripping streams