Memori and Memary
These are direct competitors offering similar SQL-based memory persistence layers for LLM agents, with MemoriLabs' implementation achieving significantly broader adoption and maintenance based on download and star metrics.
About Memori
MemoriLabs/Memori
SQL Native Memory Layer for LLMs, AI Agents & Multi-Agent Systems
Automatically intercepts and persists LLM conversations to SQL, then intelligently retrieves relevant context on subsequent queries—achieving 81.95% accuracy on long-context tasks while reducing token usage to ~5% of full-context approaches. Integrates directly with OpenAI, Anthropic, and other LLM providers via SDK wrappers, plus hooks into OpenClaw agents and MCP-compatible tools (Claude Code, Cursor) without requiring code changes. Supports bring-your-own-database deployments for self-hosted setups alongside cloud-hosted options.
About Memary
kingjulio8238/Memary
The Open Source Memory Layer For Autonomous Agents
Implements a multi-layered memory architecture combining episodic memory streams, entity knowledge graphs (via FalkorDB or Neo4j), and dynamic user/system personas that automatically evolve through agent interactions. Supports both local models via Ollama (Llama 3, LLaVA) and OpenAI APIs with pluggable tools, enabling developers to integrate memory into existing LlamaIndex ReAct agents or use the built-in ChatAgent implementation with minimal code changes.
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