engram-memory
★ 38
vs
dense-mem
★ 39
engram-memory vs dense-mem
engram-memory: Engram Memory provides AI agents with persistent, self-hosted memory, eliminating session-end forgetfulness and API costs. It features a three-tiered recall engine for efficient storage, search, and retrieval of semantic embeddings on your own hardware.; dense-mem: Dense-Mem is a self-hosted, durable memory layer for AI agents designed to preserve evidence, detect conflicts, and prevent silent rewriting of facts. It provides typed claims, verification gates, server-side embeddings, and structured recall, enabling host LLMs to focus on conversation and judgment while Dense-Mem manages memory state.
01
TL;DR
engram-memoryMemory & Context · ★ 38
Providing long-term memory for AI agents (e.g., Claude Code, Cursor) to remember codebase details, user preferences, and architectural decisions across sessions.
dense-memMemory & Context · ★ 39
Providing durable and verifiable memory for AI agents in complex tasks.
02
Side-by-Side Comparison
Field
engram-memorydense-memCategory
Memory & Context
Memory & Context
Stars
★ 38
★ 39
License
NOASSERTION
Apache-2.0
Install Command
docker run -d --name engram-memory --restart unless-stopped -p 6333:6333 -p 11435:11435 -p 8585:8585 -v engram_data:/data engrammemory/engram-memory:latest
mkdir dense-mem-local && cd dense-mem-local && curl -fsSLo docker-compose.yml https://raw.githubusercontent.com/markhuangai/dense-mem/main/examples/docker-compose.base.yml && curl -fsSLo .env.example https://raw.githubusercontent.com/markhuangai/dense-mem/main/examples/.env.example && cp .env.example .env && docker compose up -d
Updated
4mo ago
1d ago
Open Source
Yes
Yes
Tags
AI Agent Memory, Self-hosted, Vector Database
AI Memory, Knowledge Graph, Conflict Detection
03
Features
engram-memory01Three-tiered recall engine (Hot-Tier Cache, Multi-Head Hash Index, Hybrid Vector Search) for fast and efficient memory retrieval.
02Persistent memory management with semantic embedding (store, search, recall, forget, consolidate) for AI agents.
03Local-first operation with self-hosted components (Qdrant, FastEmbed, MCP server) for data privacy and zero API costs.
04Kuzu-backed entity graph for tracking entities, co-retrieval patterns, and spreading activation.
05Advanced memory capabilities including conflict detection, temporal queries, and an "answer from memory" function.
06Hive Memory for multi-device sharing, enabling shared memory pools across different agents and devices.
dense-mem01First-class evidence provenance, tracing memories from source fragments to facts.
02Facts pass through typed claims, verification, and promotion gates.
03Explicit conflict detection where comparable conflicts return clarification tasks, preventing silent overwrites.
04Clear responsibility boundary: host LLM judges, Dense-Mem manages durable state, gates, and audit metadata.
05Self-hosted with operator control over storage, team isolation, API keys, and data egress boundaries.
04
Use Cases
engram-memory↳Providing long-term memory for AI agents (e.g., Claude Code, Cursor) to remember codebase details, user preferences, and architectural decisions across sessions.
↳Enabling multi-agent systems to share a common knowledge base and collaborate effectively through shared memory pools (Hive Memory).
↳Answering complex questions by synthesizing information from an agent's stored memories, both locally and optionally with cloud enhancement.
↳Auditing an agent's knowledge at specific points in time or over date ranges using temporal queries for incident analysis or historical context.
↳Storing and retrieving user preferences, facts, decisions, goals, and insights efficiently and semantically for personalized agent interactions.
dense-mem↳Providing durable and verifiable memory for AI agents in complex tasks.
↳Building enterprise AI systems that require strong data governance, auditability, and trusted knowledge.
↳Resolving conflicting information in AI knowledge bases through user clarification and structured processes.
↳Enhancing AI agent reliability and explainability by preserving evidence and preventing silent fact rewriting.
FAQ
FAQ
What is the difference between engram-memory and dense-mem?
Both engram-memory and dense-mem are in the Memory & Context category. engram-memory has 38 stars, while dense-mem has 39 stars.
Which is better, engram-memory or dense-mem?
The best choice depends on your use case. Choose engram-memory if Providing long-term memory for AI agents (e.g., Claude Code, Cursor) to remember codebase details, user preferences, and architectural decisions across sessions., and dense-mem if Providing durable and verifiable memory for AI agents in complex tasks..
Is engram-memory free or open source?
Yes, engram-memory is open source on GitHub (NOASSERTION).
Is dense-mem free or open source?
Yes, dense-mem is open source on GitHub (Apache-2.0).
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