GNO vs Elasticsearch

A comparison of GNO with Elasticsearch for document search.

Elasticsearch is an enterprise-grade distributed search engine. GNO is a local-first personal knowledge search tool. They serve different use cases.

Quick Summary

Aspect	GNO	Elasticsearch
Best for	Personal/team knowledge	Enterprise search
Unique strength	Zero-config, privacy-first	Massive scale, Kibana
Setup time	1 minute	Hours to days

Feature Comparison

Feature	GNO	Elasticsearch
Deployment	Local CLI, zero config	Server, cluster management
Privacy	100% local, offline	Network service
Setup Time	bun install -g @gmickel/gno	Hours/days
Vector Search	Built-in (sqlite-vec)	Plugin or version 8+
AI Answers	✓ Local LLM integration	✗ (needs external LLM)
Resource Usage	~500MB RAM	GB+ RAM
Scaling	Single machine	Distributed clusters
Cost	Free	License fees at scale
Query DSL	Simple CLI flags	Complex JSON DSL
Aggregations	Basic	Powerful analytics

Planned Features

Feature	GNO	Elasticsearch
Web UI	🔜 gno serve	✓ Kibana
Raycast Extension	🔜 macOS native	✗

The Key Difference

Elasticsearch is infrastructure. GNO is a tool.

# Elasticsearch: infrastructure setup
docker-compose up -d elasticsearch kibana
# Configure indices, mappings, analyzers...
# Set up ingestion pipelines...
# Configure authentication...

# GNO: immediate productivity
bun install -g @gmickel/gno
gno init ~/notes --name notes
gno index
gno query "your search"

When to Use GNO

Personal knowledge base: Your notes, papers, meeting transcripts.

gno init ~/notes --name notes
gno query "what was that thing about React performance"

Privacy-first search: Everything stays on your machine.

# No network calls, no cloud storage
gno index
gno query "confidential project details"

Developer workflows: AI-native integration with your tools.

# MCP for Claude, Cursor, Zed, Windsurf
gno mcp install --target cursor

# RAG-style answers
gno ask "how does our auth work" --answer

Team knowledge (small scale): Shared docs on a network drive or synced folder.

gno init /shared/docs --name team-docs
gno query "quarterly goals"

Quick setup: No DevOps required.

# Install and searching in under 2 minutes
bun install -g @gmickel/gno
gno init ~/Documents --name docs && gno index
gno query "budget projections"

When to Use Elasticsearch

Enterprise scale: Millions of documents, complex requirements.

{
  "settings": {
    "number_of_shards": 5,
    "number_of_replicas": 2
  }
}

Multi-tenant applications: Many users searching shared indices.

Complex analytics: Aggregations, faceted search, dashboards.

{
  "aggs": {
    "by_category": {
      "terms": { "field": "category" }
    }
  }
}

Existing infrastructure: You already run Elasticsearch.

Kibana dashboards: Visual analytics and exploration.

Resource Comparison

Resource	GNO	Elasticsearch (minimal)
RAM	~500MB	2GB+ (4GB+ recommended)
Disk	Index size ~1x docs	Index size 1.5-2x docs
CPU	Low (mostly idle)	Moderate (always running)
Network	None (local)	Required for clients
Maintenance	None	Regular ops work

Migration Considerations

If you’re considering Elasticsearch for personal/small-team use, try GNO first:

# Install
bun install -g @gmickel/gno

# Index your documents
gno init ~/Documents --name docs
gno index

# Search
gno query "your search query"

# If you need RAG answers
gno ask "summarize project status" --answer

If you outgrow GNO (millions of documents, multi-user requirements, complex analytics), Elasticsearch is there. But for personal and small-team knowledge search, GNO is simpler, faster to set up, and privacy-preserving.

Different Tools for Different Jobs

Use Case	Recommendation
Personal notes	GNO
Team docs (<10 people)	GNO
Developer second brain	GNO
E-commerce product search	Elasticsearch
Log analytics	Elasticsearch
Enterprise document search	Elasticsearch
Privacy-critical documents	GNO