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code-memory vs. Cloud-Based Code Intelligence

A comparison of local-first vs. cloud-dependent code intelligence tools.

The Fundamental Difference

code-memory Cloud Tools (Sourcegraph, Cody, Cursor)
Data Location Your machine only Their servers
Network Required No (after initial setup) Yes, always
API Key Needed No Yes
Code Leaves Your Machine Never Yes
Works Offline Yes No
Air-gapped Compatible Yes No
Telemetry Zero Varies

Feature Comparison

Core Capabilities

Feature code-memory Sourcegraph Cody Cursor
Semantic code search ✅ ✅ ✅ ✅
Symbol definitions ✅ ✅ ✅ ✅
Cross-references ✅ ✅ ✅ ✅
Git history search ✅ ✅ ✅ ✅
Documentation search ✅ ⚠️ Limited ✅ ✅
Multi-language AST ✅ ✅ ✅ ✅

Privacy & Security

Aspect code-memory Cloud Tools
Code sent to external servers ❌ Never ✅ Required
API keys to manage ❌ None ✅ Required
Telemetry/tracking ❌ Zero ⚠️ Varies
SOC 2 compliance needed ❌ No ✅ Often required
Data residency concerns ❌ None ✅ Considerations apply
Works in restricted networks ✅ Yes ❌ No

Deployment

Aspect code-memory Cloud Tools
Installation uvx code-memory Account + API key
Setup time ~1 minute Varies
Infrastructure None Their cloud or self-hosted
Air-gapped support ✅ Yes ❌ No
Self-hosted option N/A (already local) ✅ Often available

When to Choose code-memory

Ideal For:

  • Proprietary codebases — Your code never leaves your machine
  • Security-conscious organizations — Zero external data transmission
  • Air-gapped environments — Works in completely isolated networks
  • Offline development — Full functionality without internet
  • Privacy-focused developers — Zero telemetry, zero tracking
  • Quick setup — No accounts, no API keys, no configuration

Consider Cloud Tools If:

  • You need team-wide code search across repositories
  • You want cloud-based AI code generation
  • Your workflow benefits from cloud sync
  • You're comfortable with code being processed externally

Technical Deep Dive

How code-memory Stays Local

  1. Embeddings: Uses sentence-transformers running locally on your CPU/GPU
  2. Vector Search: SQLite with sqlite-vec extension — no external database
  3. Code Parsing: Tree-sitter runs entirely in-process
  4. Git Operations: Local git repository access only
  5. Model Storage: Downloaded once to ~/.cache/huggingface/

Network Activity

code-memory network footprint:
├── Initial setup only (optional):
│   └── Model download (~600MB to local cache)
└── Runtime: ZERO network calls

Compare to cloud tools which require persistent network connections for every operation.

Air-gapped Deployment

code-memory can run in completely isolated environments:

  1. Pre-download the embedding model on a connected machine
  2. Transfer the model cache directory (~/.cache/huggingface/)
  3. Install code-memory via offline pip or standalone binary
  4. Run — no network required

See AIRGAPPED.md for detailed instructions.

Cost Comparison

code-memory Cloud Tools
Monetary cost Free (MIT license) Often subscription-based
Compute cost Your hardware Their infrastructure
Hidden costs None API usage, overages
Privacy cost Zero Your code on their servers

Zero Telemetry Guarantee

code-memory contains no telemetry, no analytics, no tracking code.

This isn't a configuration option — it's architectural. The codebase has:

  • No HTTP clients for analytics
  • No usage tracking
  • No error reporting to external services
  • No "phone home" functionality

You can verify this yourself by examining the source code.

Summary

Priority Recommended Tool
Privacy & security code-memory
Offline/air-gapped work code-memory
Zero setup friction code-memory
Team collaboration Cloud tools (Sourcegraph)
Cloud AI features Cloud tools (Cody, Cursor)

code-memory is the only option that guarantees your code stays on your machine.