--- title: "stock-rnn vs cognee" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lilianweng-stock-rnn-vs-topoteretes-cognee" tools: ["lilianweng-stock-rnn", "topoteretes-cognee"] --- # stock-rnn vs cognee *GraphCanon updated Jul 11, 2026* ## Verdict Pick stock-rnn when tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction; pick cognee when tags unique to cognee: agent-memory, ai-agents, docker, knowledge-graph. [stock-rnn](https://lilianweng.github.io/lil-log) reports 2.0k GitHub stars, 673 forks, and 24 open issues, last pushed Jul 28, 2022. [cognee](https://www.cognee.ai) has 28k stars, 2.7k forks, and 620 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [stock-rnn's repository](https://github.com/lilianweng/stock-rnn) and [cognee's repository](https://github.com/topoteretes/cognee). | | [stock-rnn](/tools/lilianweng-stock-rnn.md) | [cognee](/tools/topoteretes-cognee.md) | | --- | --- | --- | | Tagline | Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings. | Cognee is the open-source AI memory platform for agents. | | Stars | 1,976 | 27,564 | | Forks | 673 | 2,737 | | Open issues | 24 | 620 | | Language | Python | Python | | Adopt for | - | When evaluating Cognee, consider its self-hosted persistence capability and the extensive support it offers through multiple programming languages (Python, Rust, TypeScript). It uses vector databases to provide efficient | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Model Training, Vector Databases | AI Agents, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [stock-rnn](/tools/lilianweng-stock-rnn.md) | [cognee](/tools/topoteretes-cognee.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1444d | 0d | | Open issues (now) | 24 | 620 | | Owner type | User | Organization | | Full report | [trust report](/tools/lilianweng-stock-rnn/trust.md) | [trust report](/tools/topoteretes-cognee/trust.md) | ## Decision facts: cognee - **Adopt for:** When evaluating Cognee, consider its self-hosted persistence capability and the extensive support it offers through multiple programming languages (Python, Rust, TypeScript). It uses vector databases to provide efficient ## Choose when ### Choose stock-rnn if… - Tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction. - Also covers Model Training. - Leaner open-issue backlog (24). ### Choose cognee if… - Tags unique to cognee: agent-memory, ai-agents, docker, knowledge-graph. - Also covers AI Agents. - cognee ships Docker support for self-hosted deployment. - - You are developing AI agents that require persistent long-term memory across different sessions. ## When NOT to use stock-rnn - Last GitHub push was 1445 days ago (dormant maintenance, Jul 28, 2022). Validate activity before betting a new project on stock-rnn. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use cognee - - Your project does not require persistent memory storage, or your agents operate fully within short-lived sessions without the need for past context. - - You are aiming for minimal setup overhead and prefer a cloud-based solution that requires less maintenance on your infrastructure side. ## Common questions ### What is the difference between stock-rnn and cognee? stock-rnn: Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.. cognee: Cognee is the open-source AI memory platform for agents.. See the comparison table for live GitHub stats and shared categories. ### When should I choose stock-rnn over cognee? Choose stock-rnn over cognee when Tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction; Also covers Model Training; Leaner open-issue backlog (24). ### When should I choose cognee over stock-rnn? Choose cognee over stock-rnn when Tags unique to cognee: agent-memory, ai-agents, docker, knowledge-graph; Also covers AI Agents; cognee ships Docker support for self-hosted deployment; - You are developing AI agents that require persistent long-term memory across different sessions. ### When should I avoid stock-rnn? Last GitHub push was 1445 days ago (dormant maintenance, Jul 28, 2022). Validate activity before betting a new project on stock-rnn. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid cognee? - Your project does not require persistent memory storage, or your agents operate fully within short-lived sessions without the need for past context. - You are aiming for minimal setup overhead and prefer a cloud-based solution that requires less maintenance on your infrastructure side. ### Is stock-rnn or cognee more popular on GitHub? cognee has more GitHub stars (27,564 vs 1,976). Stars measure visibility, not whether either tool fits your constraints. ### Are stock-rnn and cognee open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to stock-rnn or cognee? GraphCanon lists graph-backed alternatives at [stock-rnn alternatives](/tools/lilianweng-stock-rnn/alternatives) and [cognee alternatives](/tools/topoteretes-cognee/alternatives) ([stock-rnn markdown twin](/tools/lilianweng-stock-rnn/alternatives.md), [cognee markdown twin](/tools/topoteretes-cognee/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/lilianweng-stock-rnn-vs-topoteretes-cognee.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, stock-rnn or cognee? stock-rnn: Dormant. cognee: 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 stock-rnn and cognee? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [stock-rnn trust report](/tools/lilianweng-stock-rnn/trust); [cognee trust report](/tools/topoteretes-cognee/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lilianweng-stock-rnn`](/api/graphcanon/graph?tool=lilianweng-stock-rnn) - 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/_