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AI Memory Systems — Feature Comparison

Live comparison table: carsteneu.github.io/ai-memory-comparison

71 systems, 79 features, source-backed. Every ✅ links to the exact code or docs that prove it.

What this is

A feature-level comparison of memory systems for AI coding agents. 71 systems compared across 79 features on seven axes: Data Model, Search & Retrieval, Knowledge Lifecycle, Extraction Pipeline, Platform Support, Architecture, and Benchmarks. Every claim backed by a public source citation — no marketing, no inference.

Quick start

Methodology

Every ✅ requires at least one public source: README, docs, or source code. If a feature isn't documented, it's marked ❌. Code beats docs — if docs claim a feature but the implementation doesn't exist, it's ❌. Systems are re-auditable at any time via their evidence files.

Curation criteria

  1. Specifically designed for AI agent memory — not general vector DBs, not RAG frameworks
  2. Intended for coding agents — or adaptable to them (Claude Code, Codex, OpenCode, etc.)
  3. Open source — public repo with a recognized license
  4. Not abandoned — systems inactive for extended periods may be removed

Contributing

  1. Corrections: Open a PR with a link to the public source proving the correction
  2. New systems: Submit a PR with a complete evidence file — see CONTRIBUTING.md for details
  3. New features: PR with sources for ALL systems in that row

Project maintainers: corrections to your project's row get priority review.

License

CC0 — Public Domain. Copy it, fork it, use it anywhere.

Disclosure

This comparison is maintained by the author of YesMem. YesMem is listed alongside every other system and follows the same evidence rules.

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Source-backed feature comparison of memory systems for AI coding agents. No affiliation, no marketing — just facts from public docs.

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