Source: https://seerepo.com/compare/MemoriLabs/Memori/vs/run-llama/llama_index
Markdown source: https://seerepo.com/compare/MemoriLabs/Memori/vs/run-llama/llama_index.md
Description: Memori and llama_index share 8 technologies: AIOHTTP, SQLite, ipywidgets, OpenAI, sentence-transformers, tiktoken, tokenizers, and fastembed. Both are written in Python.

# Memori vs llama_index

Memori and llama_index share 8 technologies: AIOHTTP, SQLite, ipywidgets, OpenAI, sentence-transformers, tiktoken, tokenizers, and fastembed. Both are written in Python.

- [MemoriLabs/Memori](https://seerepo.com/r/MemoriLabs/Memori): Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.
- [run-llama/llama_index](https://seerepo.com/r/run-llama/llama_index): LlamaIndex is the document processing platform for AI

## What they share and what sets them apart

- In common: AIOHTTP, SQLite, ipywidgets, OpenAI, sentence-transformers, tiktoken, tokenizers, fastembed
- Only in Memori: Tokio, Postgres, rank-bm25, faiss-cpu, hf-hub, log, botocore, openclaw
- Only in llama_index: starlette, aiomysql, aiosqlite, async-lru, asyncpg, azure-search-documents, azure-storage-blob, ibm-db, pgvecto-rs, pgvector, psycopg, psycopg2-binary, pyzmq, Redis, weaviate-client, pyarrow, lancedb, oracledb, DuckDB, pymilvus, tablestore, chromadb, falkordb, MySQL, pinecone, clickhouse-connect, gcsfs, pyiceberg, pymochow, pymysql, pyobvector, s3fs, tcvectordb, typesense, ElevenLabs, anyio, graphql-core, tornado, Ray, soupsieve, tinycss2, matplotlib-inline, prompt-toolkit, matplotlib, Rich, SQLAlchemy, argon2-cffi, azure-identity, Google, google-auth-httplib2, google-auth-oauthlib, cryptography, pyjwt, msal, einops, firecrawl-py, guardrails-ai, llama-index-core, mem0ai, opencv-python, PaddlePaddle, tavily-python, torch, transformers, ibm-watsonx-ai, cohere, LangChain, MCP, dashscope, flagembedding, nltk, sentencepiece, litellm, ModelScope, Ollama, openvino, scikit-learn, tritonclient, vLLM, datasets, exa-py, flashrank, hnswlib, langfuse, mlx, mlx-lm, nomic, optimum, paddleocr, peft, presidio-analyzer, beautifulsoup4, bleach, markupsafe, mistune, nbformat, newspaper3k, xlrd, pillow, bs4, html2text, unstructured, defusedxml, jinja2, lxml, pymupdf, filetype, docx2txt, markdownify, docling, lxml-html-clean, markitdown, nbconvert, pdf2image, pdfplumber, pypdf, pypdf2, tinytag, youtube-transcript-api, jsonschema-specifications, marshmallow, referencing, rfc3339-validator, Pydantic, docling-core, annotated-types, jsonschema, pydantic-core, opentelemetry-api, opentelemetry-semantic-conventions, prometheus-client, psutil, python-json-logger, boto3, docker, Alibaba Cloud, OpenTelemetry

## Side by side

| | Memori | llama_index |
|---|---|---|
| Size | 67,519 lines written, 242 code files | 473,236 lines written, 2,055 code files |
| Who writes it | 2.5% of its commits signed by AI. With GitHub Copilot, Claude Code, and Cursor | 0.2% of its commits signed by AI. With Claude Code, Cursor, and GitHub Copilot |
| Activity | Last push October 3, 2026, 568 commits, 17,448 stars | Last push November 5, 2026, 7,963 commits, 52,820 stars |
| Tests | 198 test files. 22.7% of its code files have a test that imports them | 1,607 test files. 46.5% of its code files have a test that imports them |

- Size: Lines written by people and agents, without generated ones; code files, without tests.
- Who writes it: A commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
- Activity: From GitHub and its history, on the day SeeRepo read it.
- Tests: The files that test the code, and the share of code files a test imports.

## Frequently asked questions

### Which is bigger, Memori or llama_index?

llama_index, with 473,236 lines written; Memori has 67,519.

The proof: [run-llama/llama_index's code at commit 444fdf0](https://github.com/run-llama/llama_index/tree/444fdf0684707de62ebb447d658dba137dd9cb99)

### Which has more GitHub stars, Memori or llama_index?

llama_index, with 52,820 stars; Memori has 17,448.

The proof: [run-llama/llama_index on GitHub](https://github.com/run-llama/llama_index)

### Which has more tests, Memori or llama_index?

llama_index, with 1,607 test files; Memori has 198.

The proof: [run-llama/llama_index's code at commit 444fdf0](https://github.com/run-llama/llama_index/tree/444fdf0684707de62ebb447d658dba137dd9cb99)

### Which was updated more recently, Memori or llama_index?

llama_index: its last push was on November 5, 2026, and Memori's on October 3, 2026.

The proof: [run-llama/llama_index's commits on GitHub](https://github.com/run-llama/llama_index/commits)

### Which has more commits signed by AI, Memori or llama_index?

Memori: an AI signed 2.5% of its commits, with GitHub Copilot, Claude Code, and Cursor; in llama_index, 0.2%.

## Sources

- MemoriLabs/Memori: Read on November 7, 2026, at commit 574b1ea (https://github.com/MemoriLabs/Memori/tree/574b1ea3e876f100ef82c37817d603eb7e258e59)
- run-llama/llama_index: Read on November 5, 2026, at commit 444fdf0 (https://github.com/run-llama/llama_index/tree/444fdf0684707de62ebb447d658dba137dd9cb99)

## What is your repo built with?

Any public repo, with no account: https://seerepo.com/r/owner/repo/built, with the owner and name it has on GitHub.