AgentIndex icon
AgentIndex
cuba-memorys logo
cuba-memorys
★ 30
vs
samyama-graph logo
samyama-graph
★ 184

cuba-memorys vs samyama-graph

cuba-memorys: Cuba-Memorys is a Model Context Protocol (MCP) server that gives AI coding assistants long-term persistent memory. It uses a knowledge graph, neuroscience-inspired algorithms like FSRS-6 adaptive decay, Hebbian learning, and dual-strength memory, along with anti-hallucination grounding. The latest version 2.0.0 is a complete Rust rewrite with 12 tools and sub-millisecond performance.; samyama-graph: Samyama is a graph-vector database written in Rust. It supports OpenCypher queries, Redis protocol, vector search, and graph algorithms. It can handle billions of edges on a single machine.

01

TL;DR

cuba-memorys logo
cuba-memorysRAG / Knowledge Base · ★ 30

Persistent learning from project context: store and retrieve entities, observations, and relations

Read cuba-memorys full review →
samyama-graph logo
samyama-graphRAG / Knowledge Base · ★ 184

Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.)

Read samyama-graph full review →
02

Side-by-Side Comparison

Field
cuba-memorys logocuba-memorys
samyama-graph logosamyama-graph
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 30
★ 184
License
NOASSERTION
Apache-2.0
Install Command
git clone https://github.com/LeandroPG19/cuba-memorys.git && cd cuba-memorys && docker compose up -d && cd rust && cargo build --release
git clone https://github.com/samyama-ai/samyama-graph && cd samyama-graph && cargo build --release
Updated
2d ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
ai-memory, ai-tools, anti-hallucination
billion-edges, cypher, cypher-query-language
03

Features

cuba-memorys logocuba-memorys
01Knowledge graph with typed relations and Leiden community detection
02FSRS-6 adaptive spaced repetition and Hebbian/BCM metaplasticity
034-signal entropy-routed RRF fusion search (TF-IDF, pg_trgm, full-text, pgvector HNSW)
04Anti-hallucination verification with graduated confidence scoring
05REM Sleep autonomous consolidation and dual-strength memory model
samyama-graph logosamyama-graph
01OpenCypher queries
02Redis protocol
03Vector search (HNSW)
04Graph algorithms (PageRank, BFS, etc.)
05Natural language queries (NLQ)
04

Use Cases

cuba-memorys logocuba-memorys
↳Persistent learning from project context: store and retrieve entities, observations, and relations
↳Error memory: record and detect repeated mistakes, preventing re-occurrence
↳Anti-hallucination grounding: verify agent claims against stored knowledge before responding
samyama-graph logosamyama-graph
↳Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.)
↳Multi-hop graph traversals
↳Cross-knowledge graph aggregation
FAQ

FAQ

What is the difference between cuba-memorys and samyama-graph?
Both cuba-memorys and samyama-graph are in the RAG / Knowledge Base category. cuba-memorys has 30 stars, while samyama-graph has 184 stars.
Which is better, cuba-memorys or samyama-graph?
The best choice depends on your use case. Choose cuba-memorys if Persistent learning from project context: store and retrieve entities, observations, and relations, and samyama-graph if Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.).
Is cuba-memorys free or open source?
Yes, cuba-memorys is open source on GitHub (NOASSERTION).
Is samyama-graph free or open source?
Yes, samyama-graph is open source on GitHub (Apache-2.0).
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