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Home Tag langsmith

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LAYER 1 (Primary keyword entities): LangChain vs LlamaIndex 2026 production decision matrix comparison diagram produced by Mohammed Shehu Ahmed at RankSquire.com (Wikidata Q138808708 / Q138808593). Shows two-column architecture comparison: LangGraph stateful orchestration (PostgreSQL checkpointing, max_loops=15, tool calling, human-in-the-loop approvals) versus LlamaIndex retrieval engine (hybrid search, 300+ connectors via LlamaHub, query decomposition, node relationships and metadata filtering). Center shows hybrid sovereign stack integration where LlamaIndex serves as named retrieval tool inside LangGraph agent. LAYER 2 (Relationships and data): Key production metrics shown: LangGraph framework overhead approximately 14 milliseconds and 2,400 tokens per request versus LlamaIndex approximately 6 milliseconds and 1,600 tokens. Token overhead gap of approximately 800 tokens produces $2,400 per month cost difference at 10 million requests per month using GPT-4o-mini pricing. Hybrid sovereign stack SVS Sovereign Viability Score 9.0 or higher combining both frameworks. LangGraph 1.0 released October 2025 with stable PostgreSQL checkpointing. LlamaIndex requires 30 to 40 percent less code than LangChain for equivalent RAG pipelines. LAYER 3 (What it proves): This architecture diagram demonstrates that LangChain and LlamaIndex solve different operational layers and are not direct competitors. LangChain via LangGraph dominates stateful orchestration while LlamaIndex dominates retrieval quality. The hybrid sovereign stack combining both on self-hosted Hetzner Frankfurt infrastructure with Qdrant vector storage and Langfuse observability costs approximately $150 to $220 per month versus $500 to $800 per month for managed equivalents. May 2026. RankSquire.com.

LangChain vs LlamaIndex 2026: The production architecture decision matrix every CTO needs

by Mohammed Shehu Ahmed

Here Is Your Answer in 60 SecondsWhy Every Existing Comparison Gets This WrongWhat LangChain and LlamaIndex Actually Are in 2026The ...

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