autobrr vs Jackett vs Prowlarr: Best Download Automation Tools 2026

If you run a self-hosted media server or download automation setup, manually searching for torrents and Usenet releases quickly becomes tedious. The right download automation tool sits between indexers and your download clients, handling everything from RSS polling to release filtering — and in autobrr’s case, catching releases the instant they’re announced on IRC channels.

In this guide, we compare three popular self-hosted download automation tools — autobrr, Jackett, and Prowlarr — examining their architectures, supported protocols, filter capabilities, and how they integrate with the broader *arr ecosystem.

Why Self-Host Download Automation

Cloud-based torrent search engines and Usenet indexer aggregators are convenient, but they come with tradeoffs:

• Release speed: IRC-based tools like autobrr catch releases within seconds of announcement — far faster than RSS polling intervals
• Indexer diversity: Self-hosted tools connect to both public and private trackers, many of which don’t offer public APIs
• Privacy: Your search queries and download patterns never leave your own server
• Fine-grained filtering: Set custom rules for resolution, codec, group, file size, and more — reducing manual sorting
• Automation pipeline: Chain indexers → download clients → media managers for fully hands-off operation
• No rate limits: Self-hosted tools don’t impose the API rate limits that cloud services do

Whether you’re running a personal media library or managing downloads for a household, the right automation layer saves hours of manual searching every week.

autobrr — IRC-Based Release Catcher

autobrr is the modern successor to autodl-irssi. Instead of polling RSS feeds on a schedule, it connects to IRC announce channels on torrent trackers and catches releases the instant they’re announced. This gives it a significant speed advantage — you can start downloading a release within seconds of it appearing on the tracker, before RSS-based tools even know it exists.

How autobrr Works

autobrr listens to IRC channels where trackers broadcast new torrent uploads. When a release announcement matches one of your configured filters, autobrr immediately sends a download request to your configured download client (qBittorrent, Deluge, Transmission, rTorrent, or Sabnzbd for Usenet). It can also send webhooks to Sonarr, Radarr, and other *arr applications.

Key features:

• Real-time IRC parsing: Parses announce messages from 100+ supported trackers
• Advanced filter engine: Match by category, resolution, codec, group, size, tags, and more
• Multi-client support: qBittorrent, Deluge, Transmission, rTorrent, Sabnzbd, and more
• Web UI: Modern React-based dashboard for managing filters and networks
• External actions: Webhooks, exec commands, and email notifications on match
• Lightweight: Written in Go, uses minimal CPU and memory

autobrr Docker Setup

Here’s a production-ready Docker Compose configuration for autobrr:

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version: "3.8"

services:
  autobrr:
    image: ghcr.io/autobrr/autobrr:latest
    container_name: autobrr
    restart: unless-stopped
    ports:
      - "7474:7474"
    volumes:
      - ./autobrr-config:/config
    environment:
      - TZ=UTC

For users who prefer PostgreSQL over SQLite:

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version: "3.8"

services:
  autobrr:
    image: ghcr.io/autobrr/autobrr:latest
    container_name: autobrr
    restart: unless-stopped
    ports:
      - "7474:7474"
    volumes:
      - ./autobrr-config:/config
    environment:
      - TZ=UTC
      - AUTOBRR__DATABASE_TYPE=postgres
      - AUTOBRR__POSTGRES_HOST=postgres
      - AUTOBRR__POSTGRES_PORT=5432
      - AUTOBRR__POSTGRES_USER=autobrr
      - AUTOBRR__POSTGRES_PASS=your_secure_password
      - AUTOBRR__POSTGRES_DATABASE=autobrr

  postgres:
    image: postgres:16-alpine
    container_name: autobrr-postgres
    restart: unless-stopped
    volumes:
      - postgres-data:/var/lib/postgresql/data
    environment:
      - POSTGRES_USER=autobrr
      - POSTGRES_PASSWORD=your_secure_password
      - POSTGRES_DB=autobrr

volumes:
  postgres-data:

After starting the containers, access the web UI at http://your-server:7474. The initial setup wizard guides you through adding IRC networks, configuring download clients, and creating your first filters.

autobrr Filter Configuration

Filters are the core of autobrr. Here’s an example filter that catches 1080p BluRay releases from specific groups:

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Filter Name: Movies 1080p BluRay
Categories: movies
Resolutions: 1080p
Sources: BluRay
Codecs: x264, x265, HEVC
Match Groups: SPARKS, DRONES, B0MBARDiERS, GECKOS
Min Size: 4 GB
Max Size: 20 GB
External: Webhook to Radarr

You can also use regular expressions for more advanced matching, and set up actions like “reject if already downloaded within 24 hours” to avoid duplicates.

Jackett — Torznab/Newznab Proxy

Jackett is the veteran of the three tools. It acts as a bridge between torrent/Usenet trackers and applications that support the Torznab or Newznab API standards. Instead of each application needing its own tracker-specific code, Jackett provides a unified API that works with any Torznab-compatible client.

How Jackett Works

Jackett maintains a library of indexer definitions — essentially scraper configurations for hundreds of trackers. When an application sends a search query to Jackett’s Torznab API, Jackett translates it into the specific format each tracker requires, aggregates the results, and returns them in a standardized XML format.

Key features:

• 400+ indexers: Supports both public and private trackers, plus Usenet indexers
• Torznab/Newznab API: Standard API that any compatible client can use
• RSS feeds: Provides per-indexer and combined RSS feeds for polling
• Web UI: Dashboard for configuring indexers and testing searches
• Caching: Caches results to reduce API calls and speed up repeated searches
• Cross-platform: Runs on Windows, Linux, and macOS

Jackett Docker Setup

Jackett is available via the LinuxServer.io image, which provides a consistent and well-maintained container:

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version: "3.8"

services:
  jackett:
    image: lscr.io/linuxserver/jackett:latest
    container_name: jackett
    restart: unless-stopped
    environment:
      - PUID=1000
      - PGID=1000
      - TZ=UTC
      - AUTO_UPDATE=true
    ports:
      - "9117:9117"
    volumes:
      - ./jackett-config:/config
      - ./jackett-downloads:/downloads

After startup, access Jackett at http://your-server:9117. Add your tracker credentials through the web UI, then copy the Torznab API URL and key into your *arr applications or download clients.

Using Jackett with Sonarr/Radarr

Once Jackett is configured with your trackers, each indexer provides a Torznab feed URL. In Sonarr or Radarr:

1. Go to Settings → Indexers → Add → Torznab → Custom
2. Paste the Torznab URL from Jackett (format: http://jackett:9117/api/v2.0/indexers/INDEXER/results/torznab)
3. Enter the API key from Jackett’s dashboard
4. Configure category mappings (e.g., Movies → 2000/2010/2020 for HD/SD/4K)
5. Test the connection and save

This gives Sonarr and Radarr access to all your trackers through a single API endpoint.

Prowlarr — The *arr Native Indexer Manager

Prowlarr was created by the Radarr team to solve a specific problem: managing indexers across multiple *arr applications was tedious and error-prone. Prowlarr centralizes indexer configuration and automatically syncs settings to all connected *arr apps.

How Prowlarr Works

Prowlarr shares the same .NET/ReactJS architecture as Sonarr, Radarr, and Lidarr. You configure your indexers once in Prowlarr, and it pushes those configurations to all connected applications via their APIs. This means adding a new tracker in Prowlarr instantly makes it available in Sonarr, Radarr, Lidarr, Readarr, and any other connected *arr app.

Key features:

• Centralized management: Configure indexers in one place, sync to all *arr apps
• *Native arr integration: Built by the same team, shares the same UI patterns
• Indexer categories: Automatic category mapping for movies, TV, music, books, and anime
• Push notifications: Alert on indexer errors, captchas, or authentication failures
• Stats dashboard: Track search success rates, failures, and response times per indexer
• Proxy support: Built-in SOCKS and HTTP proxy configuration for restricted networks

Prowlarr Docker Setup

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version: "3.8"

services:
  prowlarr:
    image: lscr.io/linuxserver/prowlarr:latest
    container_name: prowlarr
    restart: unless-stopped
    environment:
      - PUID=1000
      - PGID=1000
      - TZ=UTC
    ports:
      - "9696:9696"
    volumes:
      - ./prowlarr-config:/config

After Prowlarr starts at http://your-server:9696, connect it to your *arr applications:

1. In Prowlarr, go to Settings → Apps → Add
2. Select the application type (Sonarr, Radarr, etc.)
3. Enter the API URL and key from the target application
4. Test the connection and save

Once connected, any indexer you add in Prowlarr is automatically pushed to the connected apps.

Feature Comparison

Which Tool Should You Choose?

Choose autobrr if:

• Speed is your priority: You want releases within seconds of announcement, not minutes or hours
• You use private trackers: Many private trackers announce exclusively on IRC channels
• You want fine-grained filtering: The IRC-based filter engine supports complex rules including group matching, regex, and size ranges
• You’re migrating from autodl-irssi: autobrr is the modern replacement with a web UI and active development

Choose Jackett if:

• You need maximum indexer coverage: With 400+ supported indexers, Jackett has the broadest tracker library
• *You use non-arr applications: Any Torznab-compatible client works with Jackett (SickChill, CouchPotato, etc.)
• You prefer a proven, mature tool: Jackett has been around since 2015 with a large user base
• You want a single search API: Aggregate searches across all your trackers in one place

Choose Prowlarr if:

• *You’re deep in the arr ecosystem: Running Sonarr + Radarr + Lidarr + Readarr? Prowlarr saves you from configuring indexers four times
• You want centralized management: Add an indexer once and it appears everywhere automatically
• You prefer native integration: Prowlarr shares the same codebase patterns as the *arr apps, making it feel like part of the suite
• You need indexer health monitoring: Prowlarr tracks indexer performance and alerts you to failures

The Power Combo

Many power users run both autobrr and Prowlarr (or Jackett). autobrr handles real-time IRC announcements for the fastest possible grab, while Prowlarr manages the indexer sync across all *arr applications for everything that autobrr doesn’t catch. This gives you the best of both worlds: speed and breadth.

For a complete media automation stack, you’d typically combine these tools with a torrent client like qBittorrent and a media management setup using Sonarr and Radarr.

Complete Stack Docker Compose

Here’s a combined Docker Compose file that runs autobrr, Prowlarr, and qBittorrent together:

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version: "3.8"

services:
  autobrr:
    image: ghcr.io/autobrr/autobrr:latest
    container_name: autobrr
    restart: unless-stopped
    ports:
      - "7474:7474"
    volumes:
      - ./autobrr-config:/config
    environment:
      - TZ=UTC
    networks:
      - automation

  prowlarr:
    image: lscr.io/linuxserver/prowlarr:latest
    container_name: prowlarr
    restart: unless-stopped
    environment:
      - PUID=1000
      - PGID=1000
      - TZ=UTC
    ports:
      - "9696:9696"
    volumes:
      - ./prowlarr-config:/config
    networks:
      - automation

  qbittorrent:
    image: lscr.io/linuxserver/qbittorrent:latest
    container_name: qbittorrent
    restart: unless-stopped
    environment:
      - PUID=1000
      - PGID=1000
      - TZ=UTC
      - WEBUI_PORT=8080
    ports:
      - "8080:8080"
      - "6881:6881"
      - "6881:6881/udp"
    volumes:
      - ./qbittorrent-config:/config
      - ./downloads:/downloads
    networks:
      - automation

networks:
  automation:
    driver: bridge

All three services share a Docker network, allowing them to communicate using container names (e.g., http://qbittorrent:8080 from autobrr’s perspective).

FAQ

Can autobrr work without Prowlarr or Jackett?

Yes. autobrr is fully standalone. It connects directly to IRC networks for real-time release announcements and sends downloads to any supported client (qBittorrent, Deluge, Transmission, rTorrent, Sabnzbd). You don’t need Prowlarr or Jackett for autobrr to function — they serve different purposes in the automation pipeline.

Does Prowlarr replace Jackett?

Not entirely. Prowlarr and Jackett overlap in indexer management, but they serve different use cases. Prowlarr is designed specifically for the *arr ecosystem and automatically syncs indexer configs to connected apps. Jackett provides a Torznab/Newznab API that works with any compatible application, not just *arr tools. If you only use *arr apps, Prowlarr is more convenient. If you use other Torznab-compatible clients, Jackett is necessary.

Is autobrr faster than RSS-based tools?

Significantly. RSS feeds typically update every 5-30 minutes depending on the indexer. autobrr parses IRC announcements in real-time, often catching releases within 1-5 seconds of the tracker announcing them. For competitive private trackers where the best releases get snatched quickly, this speed difference is critical.

Can I run all three tools together?

Yes, and many users do. autobrr handles real-time IRC-based downloads, Prowlarr manages indexer sync across *arr applications, and Jackett can serve as a fallback Torznab API for applications that Prowlarr doesn’t support natively. Just be aware that running all three uses more resources than any single tool.

Do I need a VPN with these tools?

It depends on your jurisdiction and the trackers you use. For public torrents, a VPN is recommended to protect your privacy. For private trackers, many require that you use a VPN to access their IRC announce channels. Most Docker setups route torrent client traffic through a VPN container (like Gluetun) while keeping the management UIs on the local network.

What download clients does autobrr support?

autobrr supports qBittorrent, Deluge (v1 and v2), Transmission, rTorrent, Sabnzbd, and generic webhook actions. The qBittorrent integration is the most mature and recommended for most users. You can configure multiple download clients with different rules — for example, sending movies to qBittorrent and Usenet releases to Sabnzbd.

How do I migrate from autodl-irssi to autobrr?

autobrr provides a migration path from autodl-irssi. The IRC network configurations and filter rules use similar concepts, though the syntax differs. autobrr’s web UI makes migration easier — you can recreate your autodl-irssi filters visually and test them against live announce messages. The autobrr documentation includes a migration guide with step-by-step instructions.