A side-by-side of two agent frameworks for building AI agents — live GitHub data, languages, and what each is best at.
Short answer: DSPy leads Google ADK vs DSPy by community traction (★ 37k vs ★ 21k). Pick Google ADK for multi-agent systems; pick DSPy for prompt optimization.
✓ Live data verified
| Google ADK | DSPy | |
|---|---|---|
| GitHub stars | ★ 21k | ★ 37k |
| Language | Python | Python |
| Category | Agent frameworks | Agent frameworks |
| Best for | multi-agent systems | prompt optimization |
| Repository | google/adk-python | stanfordnlp/dspy |
Google ADK and DSPy are both credible choices. By community traction, DSPy leads (★ 37k). Pick Google ADK for multi-agent systems; pick DSPy for prompt optimization.
Both are credible agent frameworks. By community traction DSPy leads (★ 37k). Pick Google ADK for multi-agent systems; pick DSPy for prompt optimization.
Google ADK is Google's Agent Development Kit — a code-first, model-agnostic toolkit for building, evaluating, and deploying multi-agent systems. Optimized for Gemini.. DSPy is Programming — not prompting — language models: compile declarative pipelines into optimized prompts/weights..
DSPy has more — ★ 37k vs ★ 21k (live counts).
Often yes — many teams combine agent frameworks. Check each tool's docs for interop; they solve overlapping but not identical problems.
Google ADK is primarily Python; DSPy is primarily Python.
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