Andreas Kollegger akollegger

Aspect	Graph RAG	Graphiti
Primary Use	Static data summarization	Dynamic real-time data
Data Handling	Batch-oriented	Continuous, incremental updates
Knowledge Structure	Entity clusters & community summaries	Three-tiered: episodes, semantic entities, communities
Retrieval Method	Multiple sequential LLM calls	Hybrid (cosine, BM25, breadth-first), no LLM summarizations required
Adaptability	Low	High
Temporal Handling	Basic timestamp metadata	Rich temporal metadata
Contradiction Handling	Limited to LLM’s judgement during summarization	Edge invalidation with temporal tracking
Query Latency	Seconds to tens of seconds	Hundreds of milliseconds
Custom Entity Types	No	Yes, highly customizable

I hereby claim:

To claim this, I am signing this object:

	from dataclasses import dataclass, field
	import csv
	import json
	import os
	import pathlib
	import sys
	import typing

	from icecream import ic
	from tqdm import tqdm

	class GraphElementEncoder(json.JSONEncoder):
	def default(self,obj):
	if isinstance(obj, graph.Node):
	return {
	"element_id": obj.element_id,
	"labels": list(obj.labels),
	"properties": {k:v for k,v in obj.items()}
	}
	elif isinstance(obj, graph.Relationship):
	return {

	// gram is a lightweight graph exchange format.
	//
	// gram is a series of path updates.
	//
	// identified path elements may be introduced and referenced in a later update

	// node shapes
	() // anonymous node
	(a) // identified node
	(1) // numerically identified node

	<div id="container"></div>
	<div id="menu">
	<button id="table">TABLE</button>
	<button id="sphere">SPHERE</button>
	<button id="helix">HELIX</button>
	<button id="grid">GRID</button>
	</div>

	license: gpl-3.0
	height: 600

	license: gpl-3.0
	height: 600

	license: gpl-3.0
	height: 600