Comparison
llm-app vs spiceai
Verdict
Pick llm-app if llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz; pick spiceai if spiceAI is designed for real-time analytics and operates in Rust to integrate seamlessly with operational databases.
Markdown twin · llm-app alternatives · spiceai alternatives
GraphCanon updated 5d
Trust & integrity
| Signal | llm-app | spiceai |
|---|---|---|
| Maintenance | Steady (41d since push) As of 5d · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 5d · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- llm-app
- Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.
- spiceai
- A real-time analytics node for data-grounded AI applications
Stars
- llm-app
- 59k
- spiceai
- 3.0k
Forks
- llm-app
- 1.5k
- spiceai
- 212
Open issues
- llm-app
- 8
- spiceai
- 424
Language
- llm-app
- Jupyter Notebook
- spiceai
- Rust
Adopt for
- llm-app
- llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz
- spiceai
- SpiceAI is designed for real-time analytics and operates in Rust to integrate seamlessly with operational databases.
Persona
- llm-app
- -
- spiceai
- -
Runtime
- llm-app
- -
- spiceai
- -
License
- llm-app
- MIT
- spiceai
- Apache-2.0
Last pushed
- llm-app
- Jul 5, 2026
- spiceai
- Jul 25, 2026
Categories
- llm-app
- Data & Retrieval, LLM Frameworks, Vector Databases
- spiceai
- Data & Retrieval, LLM Frameworks
Trust and health
Maintenance
- llm-app
- Steady (60%)
- spiceai
- Very active (96%)
Days since push
- llm-app
- 41d
- spiceai
- 0d
Open issues (now)
- llm-app
- 8
- spiceai
- 424
Stars delta
- llm-app
- +11 (30d)
- spiceai
- Unknown
Open issues delta
- llm-app
- -2 (30d)
- spiceai
- Unknown
Full report
- llm-app
- Trust report
- spiceai
- Trust report
Choose llm-app if…
- llm-app is primarily Jupyter Notebook; spiceai is Rust.
- License: llm-app is MIT, spiceai is Apache-2.0.
- Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others..
- Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation.
- Also covers Vector Databases.
- - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.
When NOT to use llm-app
- - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app.
- - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.
Choose spiceai if…
- spiceai is primarily Rust; llm-app is Jupyter Notebook.
- License: spiceai is Apache-2.0, llm-app is MIT.
- Tags unique to spiceai: accelerated sql, llm-inference, operational database integration, real-time analytics.
- spiceai ships Docker support for self-hosted deployment.
- When you need real-time data-grounded AI applications that require fast SQL query execution, search capabilities, or LLM-inference
When NOT to use spiceai
- If your project already has a robust solution for real-time analytics that does not benefit from being rewritten in Rust
- Where the ecosystem preference is not Rust, as SpiceAI's accelerated query engine and integration features are tied closely with Rust
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (pathwaycom/llm-app) · observed Aug 16, 2026
- GitHub forks (pathwaycom/llm-app) · observed Aug 16, 2026
- Last push (pathwaycom/llm-app) · observed Jul 5, 2026
- License file (MIT) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (spiceai/spiceai) · observed Jul 25, 2026
- GitHub forks (spiceai/spiceai) · observed Jul 25, 2026
- Last push (spiceai/spiceai) · observed Jul 25, 2026
- License file (Apache-2.0) · observed Jul 25, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: llm-app 59k · spiceai 3.0k (synced Aug 16, 2026).
Common questions
- What is the difference between llm-app and spiceai?
- llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. spiceai: A real-time analytics node for data-grounded AI applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose llm-app over spiceai?
- Choose llm-app over spiceai when llm-app is primarily Jupyter Notebook; spiceai is Rust; License: llm-app is MIT, spiceai is Apache-2.0; Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation; Also covers Vector Databases; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.
- When should I choose spiceai over llm-app?
- Choose spiceai over llm-app when spiceai is primarily Rust; llm-app is Jupyter Notebook; License: spiceai is Apache-2.0, llm-app is MIT; Tags unique to spiceai: accelerated sql, llm-inference, operational database integration, real-time analytics; spiceai ships Docker support for self-hosted deployment; When you need real-time data-grounded AI applications that require fast SQL query execution, search capabilities, or LLM-inference.
- When should I avoid llm-app?
- - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.
- When should I avoid spiceai?
- If your project already has a robust solution for real-time analytics that does not benefit from being rewritten in Rust Where the ecosystem preference is not Rust, as SpiceAI's accelerated query engine and integration features are tied closely with Rust
- Is llm-app or spiceai more popular on GitHub?
- llm-app has more GitHub stars (59,037 vs 3,047). Stars measure visibility, not whether either tool fits your constraints.
- Are llm-app and spiceai open source?
- Yes - both are open-source projects on GitHub (llm-app: MIT, spiceai: Apache-2.0).
- Where can I find alternatives to llm-app or spiceai?
- GraphCanon lists graph-backed alternatives at llm-app alternatives and spiceai alternatives (llm-app markdown twin, spiceai markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, llm-app or spiceai?
- llm-app: Steady. spiceai: 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 llm-app and spiceai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm-app trust report; spiceai trust report.