--- title: "haystack vs aqueduct" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deepset-ai-haystack-vs-runllm-aqueduct" tools: ["deepset-ai-haystack", "runllm-aqueduct"] --- # haystack vs aqueduct *GraphCanon updated Aug 3, 2026* ## Verdict Pick haystack if haystack is an open-source AI orchestration framework for building context-engineered LLM applications; pick aqueduct if aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. [haystack](https://haystack.deepset.ai) reports 26k GitHub stars, 3.0k forks, and 108 open issues, last pushed Aug 1, 2026. [aqueduct](https://aqueducthq.com) has 517 stars, 20 forks, and 11 open issues, last pushed Jun 7, 2023. Figures are from public GitHub metadata via [haystack's repository](https://github.com/deepset-ai/haystack) and [aqueduct's repository](https://github.com/RunLLM/aqueduct). | | [haystack](/tools/deepset-ai-haystack.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Tagline | Open-source AI orchestration framework for building context-engineered LLM applications. | Orchestrate LLM and ML workloads on any cloud infrastructure using Go. | | Stars | 26,073 | 517 | | Forks | 2,972 | 20 | | Open issues | 108 | 11 | | Language | Python | Go | | Adopt for | Haystack is an open-source AI orchestration framework for building context-engineered LLM applications. | Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents, Data & Retrieval, LLM Frameworks | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [haystack](/tools/deepset-ai-haystack.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1152d | | Open issues (now) | 108 | 11 | | Full report | [trust report](/tools/deepset-ai-haystack/trust.md) | [trust report](/tools/runllm-aqueduct/trust.md) | ## Decision facts: haystack - **Pricing:** freemium - 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 - **Adopt for:** Haystack is an open-source AI orchestration framework for building context-engineered LLM applications. - **License detail:** Apache-2.0 ## Decision facts: aqueduct - **Adopt for:** Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. ## Choose when ### Choose haystack if… - haystack is primarily Python; aqueduct is Go. - 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, agents, gemini, generative-ai. - Also covers AI Agents, Data & Retrieval. - You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines. ### Choose aqueduct if… - aqueduct is primarily Go; haystack is Python. - Tags unique to aqueduct: data, data-science, kubernetes, llm. - Also covers Inference & Serving, Model Training. - When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training. ## 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. ## When NOT to use aqueduct - Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. - Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives. ## Common questions ### What is the difference between haystack and aqueduct? haystack: Open-source AI orchestration framework for building context-engineered LLM applications.. aqueduct: Orchestrate LLM and ML workloads on any cloud infrastructure using Go.. See the comparison table for live GitHub stats and shared categories. ### When should I choose haystack over aqueduct? Choose haystack over aqueduct when haystack is primarily Python; aqueduct is Go; 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, agents, gemini, generative-ai; Also covers AI Agents, Data & Retrieval; You need explicit control over retrieval, routing, memory, and generation within your LLM application pipelines. ### When should I choose aqueduct over haystack? Choose aqueduct over haystack when aqueduct is primarily Go; haystack is Python; Tags unique to aqueduct: data, data-science, kubernetes, llm; Also covers Inference & Serving, Model Training; When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training. ### 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 aqueduct? Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives. ### Is haystack or aqueduct more popular on GitHub? haystack has more GitHub stars (26,073 vs 517). Stars measure visibility, not whether either tool fits your constraints. ### Are haystack and aqueduct open source? Yes - both are open-source projects on GitHub (haystack: Apache-2.0, aqueduct: Apache-2.0). ### Where can I find alternatives to haystack or aqueduct? GraphCanon lists graph-backed alternatives at [haystack alternatives](/tools/deepset-ai-haystack/alternatives) and [aqueduct alternatives](/tools/runllm-aqueduct/alternatives) ([haystack markdown twin](/tools/deepset-ai-haystack/alternatives.md), [aqueduct markdown twin](/tools/runllm-aqueduct/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/deepset-ai-haystack-vs-runllm-aqueduct.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, haystack or aqueduct? haystack: Very active. aqueduct: 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 aqueduct? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [haystack trust report](/tools/deepset-ai-haystack/trust); [aqueduct trust report](/tools/runllm-aqueduct/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=deepset-ai-haystack`](/api/graphcanon/graph?tool=deepset-ai-haystack) - 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/_