Searxng vs Metager vs Whoogle: Self-Hosted Search Compared

If you’re running local LLMs or want to strip Google out of your infrastructure entirely, you’ve probably looked at self-hosted metasearch engines. The obvious contenders are Searxng, Metager, and Whoogle. All three sit in front of multiple search engines, aggregate results, and let you own your search data. But they’re not interchangeable. I’ve run all three in my homelab over the past year, and the differences matter when you’re deciding what to actually deploy.

The Basics: What Each One Does

Searxng is a fork of Searx. It aggregates from 70+ engines (Google, Bing, DuckDuckGo, Qwant, etc.) and ships with a solid web UI. You get results from multiple sources, no tracking, no user profiling. Integrates cleanly with Open WebUI and other local LLM tools as a search backend.

Metager is a German-hosted metasearch engine that you can also self-host. It emphasizes privacy and includes its own crawler alongside aggregation. Less polished UI than Searxng. Smaller community. Fewer customization options out of the box.

Whoogle is a lighter-weight Google frontend. It doesn’t aggregate like the other two—it queries Google directly but strips tracking, ads, and JavaScript bloat. Faster load times. Minimal resource footprint. But you’re still hitting Google’s servers, just without the surveillance wrapper.

Feature Comparison Table

Feature	Searxng	Metager	Whoogle
Aggregation sources	70+	50+	Google only
Self-hostable	Yes	Yes	Yes
Docker support	Excellent	Good	Excellent
Web UI customization	High	Low	Low
LLM integration	Native (Open WebUI)	Works but awkward	Works via API
RAM requirement	512 MB+	256 MB	128 MB
CPU overhead	Moderate	Low	Very low
Active development	Yes	Sporadic	Slow
YAML configuration	Yes, extensive	Limited	Environment vars
API endpoint	JSON/CSV/RSS	JSON only	JSON

Searxng: The Full-Featured Choice

Searxng wins if you want control and aggregation. The YAML config file is extensive. You can enable or disable individual search engines, set weights, adjust result limits, customize the UI theme, change the logo, modify the color scheme. I’ve tuned my instance to hit only non-tracking sources and deprioritize any engine that hands data back to ad networks. It actually respects that configuration.

The Open WebUI integration is the real selling point. You point Open WebUI to your Searxng instance, and when your local LLM needs current information, it queries Searxng instead of making users run their own searches. This is the workflow that matters for a homelab AI setup. Your LLM stays air-gapped, but has factual grounding.

Setup is straightforward with Docker. Most people use the linuxserver image or the official image. Takes about five minutes to spin up.

version: '3.8'
services:
  searxng:
    image: searxng/searxng:latest
    container_name: searxng
    ports:
      - "8888:8080"
    volumes:
      - ./searxng:/etc/searxng
    environment:
      - SEARXNG_SECRET=your-secret-key-here
    restart: unless-stopped

The catch: Searxng uses more resources than the alternatives. On my homelab (a used HP Mini with 4GB RAM and a 4-core Celeron), spinning up Searxng with a full engine suite adds about 200-300MB of baseline RAM. Not dealbreaking, but noticeable if you’re already running Ollama, Home Assistant, and a database server.

Search latency matters too. Searxng hits multiple engines in parallel and waits for responses. Average query time on my setup is 1.2 seconds. Acceptable for manual searches, slightly slow if you’re calling it from an LLM with timeout constraints.

Metager: The Lightweight Alternative

Metager runs on less hardware. If you’re working with a Raspberry Pi 3 or a 512MB VPS, Metager won’t choke. The footprint is smaller. The UI is dated—it looks like a search engine from 2012—but it works. Results are serviceable if you’re just doing text searches.

The problem: customization is sparse. You can’t easily adjust which engines it queries. Configuration is limited. The Docker community support is thinner. If something breaks, you’re either debugging the source code or posting to a German-language forum.

I ran Metager for about three months to see if I could use it with Open WebUI. The integration works technically—you can point Open WebUI to it—but the response format isn’t optimized for LLM consumption. Results come back less structured. It felt like making something work instead of using something designed for the job.

Development is sporadic. The last meaningful update was eight months ago when I checked. Searxng gets updates every 2-3 weeks. That matters when you need security patches or compatibility fixes.

Whoogle: The Minimal Option

Whoogle is what you choose if you just want to strip ads and tracking from Google searches without changing your search behavior. It’s a thin proxy between you and Google. Extremely fast—results load in 300-400ms on my connection. Uses barely any RAM. Can run on a Raspberry Pi Zero with headroom.

But Whoogle doesn’t solve the privacy problem if you care about not hitting Google at all. Whoogle’s queries still go to Google. Google sees them. Whoogle just removes the JavaScript and ad networks that would normally track you within the result page. It’s harm reduction, not independence.

If your concern is “I want to use Google without being tracked by secondary ad networks,” Whoogle is the right answer. If your concern is “I don’t want any search queries leaving my network,” Whoogle doesn’t qualify.

The UI is cleaner than Metager’s but less customizable than Searxng’s. Docker runs reliably. LLM integration works but requires you to manually format requests—there’s no native integration like with Searxng and Open WebUI.

Which One to Actually Run

For a homelab with local LLMs: Searxng. The Open WebUI integration alone justifies it. You get aggregated results, control over what sources you trust, and seamless LLM grounding. Burn the 300MB of RAM. It’s worth it.

For ultra-low-resource setups (Raspberry Pi, minimal VPS, shared hosting): Metager if you need aggregation, Whoogle if you just want Google minus the garbage. Both will run on constrained hardware Searxng struggles with.

For privacy theater without infrastructure changes: Whoogle. You get the aesthetics of privacy and remove ad tracking without rearchitecting your search workflow. It’s a browser extension’s worth of friction instead of a full service deployment.

One thing that surprised me after running these for months: Searxng’s result quality varies wildly depending on which engines you enable. If you include too many niche engines, you get noise. I disabled 40% of sources and got better, cleaner results. Neither Metager nor Whoogle require this tuning—results are what they are. For someone just wanting a working setup without fiddling, that’s an advantage neither alternative gets credit for.

Maintenance and Updates

Searxng updates frequently. Security fixes, engine compatibility patches, UI improvements. You should plan to redeploy every month or two if you care about staying current. The official Docker image is well-maintained.

Metager is functional but neglected. If it works when you set it up, it’ll probably work in a year without touching it. But you won’t get new features or security improvements. That’s either a feature or a bug depending on your risk tolerance.

Whoogle sits in the middle. Updates arrive sporadically. The last few have been minor. It’s stable enough that I’ve seen instances running the same version for a year without issues.

Real-World Performance

I tested all three on the same hardware (Proxmox VM with 2 vCPU, 2GB allocated RAM) with identical network conditions. Same queries, same time of day, multiple runs.

Whoogle: 350ms average. Barely moves CPU or RAM. Predictable.

Metager: 800ms average. Quieter resource use than Searxng but less responsive than Whoogle.

Searxng: 1.2 seconds average. Spikier CPU usage while aggregating. Memory stable at 200MB baseline, 400MB under load.

For a local LLM calling search every few queries, the absolute speed difference doesn’t matter much. For a human doing interactive searches, Whoogle feels snappier. Searxng feels measured. Metager feels slow.

FAQ

Can Searxng run on a Raspberry Pi?

Yes, but not comfortably. A Pi 4 with 4GB RAM will work. Pi 3 will struggle. You’ll need to disable many search engines to fit the footprint. Metager or Whoogle are better choices for Pi-class hardware.

Does Searxng require an internet connection?

Searxng itself runs locally, but it aggregates from external search engines. You need internet to query those sources. If you want completely air-gapped search, you need a different solution like Milvus with local embeddings.

Which search engine integration works best with Open WebUI?

Searxng. It’s designed for this workflow. Open WebUI explicitly supports Searxng as a search backend. Metager and Whoogle work but require additional configuration and don’t integrate as smoothly.

Is Metager safer than Searxng for privacy?

Not inherently. Both are self-hosted, so privacy depends on where you run them. Neither logs queries by default. Metager is German and subject to German privacy law, which some people view as stronger. But that’s geopolitical preference, not technical advantage.

How much disk space do these need?

Searxng: 500MB for Docker image, minimal persistent storage if you’re not caching results. Metager and Whoogle: similar, roughly 300-400MB each. All three are lean on disk. The bottleneck is always RAM and CPU, not storage.

Explore Searxng in our AI Homelab Toolkit.