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Jaesol Shin

Jaesol Shin

Towards observable, reliable, scalable AI

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All Posts 26 Research 1 AI 17 Development 3 DB 5

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AI8 PostgreSQL8 Benchmark7 RAG6 LLM4 zsh4 Claude Code4 OpenAI4 GraphRAG4 LightRAG4 Multi-account3 Dotfiles3 Configuration3 Developer Workflow3 API3 Productivity2 GPT-52 DeepSeek2 GraphDB2 RCTE2 Neo4j2 Apache AGE2 Recursive CTE2 Markdown2 PDF2 Agent2 Self-Improvement2 POMDP2

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2026 26

#Neo4j

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May 21, 2026 · AI

GraphDB Benchmark (2/2) — Workload Matrix and Final Recommendations

Eight graph engines measured across OLTP, memory, analytics, and differentiation queries

#GraphDB #PostgreSQL #RCTE #Neo4j

May 20, 2026 · AI

GraphDB Benchmark, Eight Engines (Part 1) — Decomposing the RCTE 290x Gap

On a 1.14M-edge knowledge-graph workload, PostgreSQL RCTE beats Apache AGE by 290x — tracing the cypher() wrapper's 13ms cost and PG plan generation accumulation

#GraphDB #PostgreSQL #RCTE #Apache AGE
Jaesol Shin

Jaesol Shin

Towards observable, reliable, scalable AI

GitHub

Categories

All Posts 26 Research 1 AI 17 Development 3 DB 5

Tags

AI8 PostgreSQL8 Benchmark7 RAG6 LLM4 zsh4 Claude Code4 OpenAI4 GraphRAG4 LightRAG4 Multi-account3 Dotfiles3 Configuration3 Developer Workflow3 API3 Productivity2 GPT-52 DeepSeek2 GraphDB2 RCTE2 Neo4j2 Apache AGE2 Recursive CTE2 Markdown2 PDF2 Agent2 Self-Improvement2 POMDP2

Archive

2026 26