--- title: "TrueMemory vs Agent_Memory_Techniques" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/buildingjoshbetter-truememory-vs-nirdiamant-agent-memory-techniques" tools: ["buildingjoshbetter-truememory", "nirdiamant-agent-memory-techniques"] --- # TrueMemory vs Agent_Memory_Techniques *GraphCanon updated Aug 23, 2026* ## Verdict Pick TrueMemory if trueMemory is an automatic capture and recall memory system for AI agents using SQLite; pick Agent_Memory_Techniques if agent_Memory_Techniques provides thirty Jupyter Notebooks that detail advanced memory techniques for LLMs. [TrueMemory](https://truememory.net) reports 373 GitHub stars, 47 forks, and 18 open issues, last pushed Jul 29, 2026. [Agent_Memory_Techniques](https://diamantai.substack.com/) has 924 stars, 120 forks, and 0 open issues, last pushed Aug 15, 2026. Figures are from public GitHub metadata via [TrueMemory's repository](https://github.com/buildingjoshbetter/TrueMemory) and [Agent_Memory_Techniques's repository](https://github.com/NirDiamant/Agent_Memory_Techniques). | | [TrueMemory](/tools/buildingjoshbetter-truememory.md) | [Agent_Memory_Techniques](/tools/nirdiamant-agent-memory-techniques.md) | | --- | --- | --- | | Tagline | Automatic capture and recall memory system for AI agents | Agent memory for LLMs: runnable Jupyter notebooks on various memory and knowledge techniques. | | Stars | 373 | 924 | | Forks | 47 | 120 | | Open issues | 18 | 0 | | Language | Python | Jupyter Notebook | | Adopt for | TrueMemory is an automatic capture and recall memory system for AI agents using SQLite. | Agent_Memory_Techniques provides thirty Jupyter Notebooks that detail advanced memory techniques for LLMs. | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 | Apache-2.0 | | Categories | AI Agents, Developer Tools | AI Agents, Evaluation & Observability, Model Training, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [TrueMemory](/tools/buildingjoshbetter-truememory.md) | [Agent_Memory_Techniques](/tools/nirdiamant-agent-memory-techniques.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 25d | 6d | | Open issues (now) | 18 | 0 | | Stars delta | +4 (30d) | +119 (30d) | | Open issues delta | +5 (30d) | -1 (30d) | | Full report | [trust report](/tools/buildingjoshbetter-truememory/trust.md) | [trust report](/tools/nirdiamant-agent-memory-techniques/trust.md) | ## Decision facts: TrueMemory - **Adopt for:** TrueMemory is an automatic capture and recall memory system for AI agents using SQLite. ## Decision facts: Agent_Memory_Techniques - **Adopt for:** Agent_Memory_Techniques provides thirty Jupyter Notebooks that detail advanced memory techniques for LLMs. ## Choose when ### Choose TrueMemory if… - TrueMemory is primarily Python; Agent_Memory_Techniques is Jupyter Notebook. - License: TrueMemory is AGPL-3.0, Agent_Memory_Techniques is Apache-2.0. - Tags unique to TrueMemory: ai-agent, embeddings, llm, model-context-protocol. - Also covers Developer Tools. - When you want to ensure your memory storage remains entirely local without depending on cloud services. ### Choose Agent_Memory_Techniques if… - Agent_Memory_Techniques is primarily Jupyter Notebook; TrueMemory is Python. - License: Agent_Memory_Techniques is Apache-2.0, TrueMemory is AGPL-3.0. - Tags unique to Agent_Memory_Techniques: ai-agents, anthropic, episodic-memory, graphiti. - Also covers Evaluation & Observability, Model Training, Vector Databases. - Need to integrate multiple types of memory systems such as episodic, semantic, or vector stores ## When NOT to use TrueMemory - If you need extensive scalability features offered by cloud-based memory solutions. - When your project mandates integration exclusively with non-SQLite databases, because TrueMemory is centered around SQLite for its backend. ## When NOT to use Agent_Memory_Techniques - Looking for a lightweight solution with minimal setup; this has extensive notebooks and dependencies - Require real-time memory management without heavy computational overhead, as some techniques are more geared toward detailed offline analysis ## Common questions ### What is the difference between TrueMemory and Agent_Memory_Techniques? TrueMemory: Automatic capture and recall memory system for AI agents. Agent_Memory_Techniques: Agent memory for LLMs: runnable Jupyter notebooks on various memory and knowledge techniques.. See the comparison table for live GitHub stats and shared categories. ### When should I choose TrueMemory over Agent_Memory_Techniques? Choose TrueMemory over Agent_Memory_Techniques when TrueMemory is primarily Python; Agent_Memory_Techniques is Jupyter Notebook; License: TrueMemory is AGPL-3.0, Agent_Memory_Techniques is Apache-2.0; Tags unique to TrueMemory: ai-agent, embeddings, llm, model-context-protocol; Also covers Developer Tools; When you want to ensure your memory storage remains entirely local without depending on cloud services. ### When should I choose Agent_Memory_Techniques over TrueMemory? Choose Agent_Memory_Techniques over TrueMemory when Agent_Memory_Techniques is primarily Jupyter Notebook; TrueMemory is Python; License: Agent_Memory_Techniques is Apache-2.0, TrueMemory is AGPL-3.0; Tags unique to Agent_Memory_Techniques: ai-agents, anthropic, episodic-memory, graphiti; Also covers Evaluation & Observability, Model Training, Vector Databases; Need to integrate multiple types of memory systems such as episodic, semantic, or vector stores. ### When should I avoid TrueMemory? If you need extensive scalability features offered by cloud-based memory solutions. When your project mandates integration exclusively with non-SQLite databases, because TrueMemory is centered around SQLite for its backend. ### When should I avoid Agent_Memory_Techniques? Looking for a lightweight solution with minimal setup; this has extensive notebooks and dependencies Require real-time memory management without heavy computational overhead, as some techniques are more geared toward detailed offline analysis ### Is TrueMemory or Agent_Memory_Techniques more popular on GitHub? Agent_Memory_Techniques has more GitHub stars (924 vs 373). Stars measure visibility, not whether either tool fits your constraints. ### Are TrueMemory and Agent_Memory_Techniques open source? Yes - both are open-source projects on GitHub (TrueMemory: AGPL-3.0, Agent_Memory_Techniques: Apache-2.0). ### Where can I find alternatives to TrueMemory or Agent_Memory_Techniques? GraphCanon lists graph-backed alternatives at [TrueMemory alternatives](/tools/buildingjoshbetter-truememory/alternatives) and [Agent_Memory_Techniques alternatives](/tools/nirdiamant-agent-memory-techniques/alternatives) ([TrueMemory markdown twin](/tools/buildingjoshbetter-truememory/alternatives.md), [Agent_Memory_Techniques markdown twin](/tools/nirdiamant-agent-memory-techniques/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/buildingjoshbetter-truememory-vs-nirdiamant-agent-memory-techniques.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, TrueMemory or Agent_Memory_Techniques? TrueMemory: Active. Agent_Memory_Techniques: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for TrueMemory and Agent_Memory_Techniques? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [TrueMemory trust report](/tools/buildingjoshbetter-truememory/trust); [Agent_Memory_Techniques trust report](/tools/nirdiamant-agent-memory-techniques/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=buildingjoshbetter-truememory`](/api/graphcanon/graph?tool=buildingjoshbetter-truememory) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_