DeepYard

DSPy vs Haystack

Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.

Direct Answer

DSPy suits teams needing open-source access, prompt optimization focus, and 37,489 GitHub stars in current listing data. Haystack suits teams needing open-source access, pipelines focus, and 26,274 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.

What this comparison weighs

  • Pricing and free-tier availability
  • License model and deployment fit
  • GitHub adoption and contributor depth
  • Catalog tags, integrations, and supported workflows
D

DSPy

Framework for programming — not prompting — LLMs — 33K+ stars

OSSFree
37.5Ktoday406
H

Haystack

End-to-end LLM framework for building NLP and agent pipelines — 18K+ stars

OSSFree
26.3K600.0K/wtoday415
MetricDSPyHaystack
GitHub Stars37.5K26.3K
Contributors406415
Last CommitAug 21, 2026Aug 22, 2026
Open Issues64395
Licenseopen-sourceopen-source
Pricingopen-sourceopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Choose DSPy if you need

  • DSPy is the stronger pick when Prompt Optimization matters because that capability is listed only on its profile.
  • DSPy shows broader GitHub adoption with 37,489 stars versus 26,274 for Haystack.
  • DSPy is the cleaner fit if you specifically need Prompt Optimization workflows from the catalog tags.

Choose Haystack if you need

  • Haystack is the stronger pick when Pipelines matters because that capability is listed only on its profile.
  • Haystack has a larger visible contributor base (415 vs 406).
  • Haystack is the cleaner fit if you specifically need Pipelines workflows from the catalog tags.

Meaningful differences

  • GitHub adoption: DSPy shows 37,489 stars versus 26,274 for Haystack.
  • Contributor count: DSPy lists 406 contributors and Haystack lists 415.

Shared capabilities

  • Rag
  • Python
  • Open Source

Shared Tags

ragpythonopen-source

Only in DSPy

prompt-optimizationprogrammingresearchstanford

Only in Haystack

pipelinesagentsnlpproduction

Limitations and evidence

  • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
  • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
  • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.

Source links

Manifest content date: 2026-08-21

About DSPy

DSPy replaces prompt engineering with programming. Instead of writing prompts, you define modules with input/output signatures and DSPy automatically optimizes the prompts and weights for your pipeline. Supports chain-of-thought, retrieval-augmented generation, and multi-hop reasoning patterns. From Stanford NLP.

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About Haystack

Haystack by deepset is a Python framework for building production-ready LLM applications, RAG pipelines, and AI agents. It provides a composable pipeline architecture where components (retrievers, generators, rankers, agents) connect through a directed graph. Haystack supports all major LLM providers and vector databases, with strong emphasis on evaluation, testing, and production deployment.

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