Comparison
haystack vs LLMStack
Verdict
Pick haystack if haystack is an open-source AI orchestration framework for building context-engineered LLM applications; pick LLMStack if lLMStack is a no-code framework designed for building LLM Agents and complex workflows with data integration, suitable for teams that want to leverage AI without deep coding expertise.
Markdown twin · haystack alternatives · LLMStack alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | haystack | LLMStack |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Dormant (612d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 4d · 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
- haystack
- Open-source AI orchestration framework for building context-engineered LLM applications.
- LLMStack
- No-code multi-agent framework to build LLM Agents, workflows and applications with your data
Stars
- haystack
- 26k
- LLMStack
- 2.3k
Forks
- haystack
- 3.0k
- LLMStack
- 347
Open issues
- haystack
- 108
- LLMStack
- 23
Language
- haystack
- Python
- LLMStack
- Python
Adopt for
- haystack
- Haystack is an open-source AI orchestration framework for building context-engineered LLM applications.
- LLMStack
- LLMStack is a no-code framework designed for building LLM Agents and complex workflows with data integration, suitable for teams that want to leverage AI without deep coding expertise.
Persona
- haystack
- -
- LLMStack
- -
Runtime
- haystack
- -
- LLMStack
- -
License
- haystack
- Apache-2.0
- LLMStack
- Other
Last pushed
- haystack
- Aug 1, 2026
- LLMStack
- Dec 11, 2024
Categories
- haystack
- AI Agents, Data & Retrieval, LLM Frameworks
- LLMStack
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- haystack
- Very active (96%)
- LLMStack
- Dormant (18%)
Days since push
- haystack
- 0d
- LLMStack
- 612d
Open issues (now)
- haystack
- 108
- LLMStack
- 23
Stars delta
- haystack
- Unknown
- LLMStack
- +2 (30d)
Open issues delta
- haystack
- Unknown
- LLMStack
- -1 (30d)
Full report
- haystack
- Trust report
- LLMStack
- Trust report
Shared compatibility
- Python · haystack: Python runtime · LLMStack: Python runtime
Choose haystack if…
- License: haystack is Apache-2.0, LLMStack is Other.
- Pricing: Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources..
- Requirements: Min 4 GB RAM; Requires Docker.
- Tags unique to haystack: agent, ai, gemini, gpt-4.
- Also covers Data & Retrieval.
- You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines.
When NOT to use haystack
- You require integration with specific proprietary tools or frameworks not supported by Haystack.
- Your development team is not familiar with Python-based technologies, since Haystack primarily supports Python-based workflows.
- You are looking for a completely managed service rather than an open-source framework that requires more hands-on configuration and customization.
Choose LLMStack if…
- License: LLMStack is Other, haystack is Apache-2.0.
- Tags unique to LLMStack: ai-agents-framework, llm-agents, llm-chain, no-code-ai.
- Use LLMStack when you need a no-code solution to develop multi-agent systems based on large language models.
When NOT to use LLMStack
- Avoid using LLMStack if your project necessitates heavy customization or fine-tuning at the coding level, as it may limit flexibility compared to code-based alternatives.
- Not recommended for teams with robust software engineering capabilities and a need for detailed control over underlying AI model architectures.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (deepset-ai/haystack) · observed Aug 1, 2026
- GitHub forks (deepset-ai/haystack) · observed Aug 1, 2026
- Last push (deepset-ai/haystack) · observed Aug 1, 2026
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (trypromptly/LLMStack) · observed Aug 16, 2026
- GitHub forks (trypromptly/LLMStack) · observed Aug 16, 2026
- Last push (trypromptly/LLMStack) · observed Dec 11, 2024
- License file (Other) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: haystack 26k · LLMStack 2.3k (synced Aug 1, 2026).
Common questions
- What is the difference between haystack and LLMStack?
- haystack: Open-source AI orchestration framework for building context-engineered LLM applications.. LLMStack: No-code multi-agent framework to build LLM Agents, workflows and applications with your data. See the comparison table for live GitHub stats and shared categories.
- When should I choose haystack over LLMStack?
- Choose haystack over LLMStack when License: haystack is Apache-2.0, LLMStack is Other; Pricing: Free and open-source under the Apache-2.0 license, but users have to manage their own infrastructure and resources.; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to haystack: agent, ai, gemini, gpt-4; Also covers Data & Retrieval; You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines.
- When should I choose LLMStack over haystack?
- Choose LLMStack over haystack when License: LLMStack is Other, haystack is Apache-2.0; Tags unique to LLMStack: ai-agents-framework, llm-agents, llm-chain, no-code-ai; Use LLMStack when you need a no-code solution to develop multi-agent systems based on large language models.
- When should I avoid haystack?
- You require integration with specific proprietary tools or frameworks not supported by Haystack. Your development team is not familiar with Python-based technologies, since Haystack primarily supports Python-based workflows. You are looking for a completely managed service rather than an open-source framework that requires more hands-on configuration and customization.
- When should I avoid LLMStack?
- Avoid using LLMStack if your project necessitates heavy customization or fine-tuning at the coding level, as it may limit flexibility compared to code-based alternatives. Not recommended for teams with robust software engineering capabilities and a need for detailed control over underlying AI model architectures.
- Is haystack or LLMStack more popular on GitHub?
- haystack has more GitHub stars (26,073 vs 2,309). Stars measure visibility, not whether either tool fits your constraints.
- Are haystack and LLMStack open source?
- Yes - both are open-source projects on GitHub (haystack: Apache-2.0, LLMStack: Other).
- Where can I find alternatives to haystack or LLMStack?
- GraphCanon lists graph-backed alternatives at haystack alternatives and LLMStack alternatives (haystack markdown twin, LLMStack 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, haystack or LLMStack?
- haystack: Very active. LLMStack: Dormant. 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 haystack and LLMStack?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: haystack trust report; LLMStack trust report.