AI tool comparison
Google ADK Python 1.0 vs Onyx
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Google ADK Python 1.0
Google's production-ready framework for building AI agents
75%
Panel ship
—
Community
Free
Entry
Google's Agent Development Kit (ADK) Python hit v1.0.0 stable on April 17, marking it production-ready for teams building and deploying AI agents at scale. ADK is a modular, code-first framework that applies standard software engineering principles to agent development — graph-based workflow execution, structured agent-to-agent delegation via a Task API, native MCP support for tool integration, and built-in evaluation tooling. Unlike LangChain's general-purpose orchestration or CrewAI's role-based crews, ADK leans into composable determinism: you define explicit graphs of agent behavior that are auditable, testable, and deployable directly to Google Cloud's Vertex AI Agent Engine. It supports Python, TypeScript, Go, and Java, making it one of the few multi-language agent frameworks in production. The 1.0 stable label matters. Google has been iterating ADK roughly every two weeks, and teams that held off on building with it due to API instability now have a stable target. With Vertex AI providing the deployment layer and Agent Engine handling orchestration at scale, this is Google's full-stack answer to the agent infrastructure question.
Developer Tools
Onyx
Self-hosted AI platform with RAG, agents, and 50+ connectors — MIT licensed
75%
Panel ship
—
Community
Paid
Entry
Onyx is a fully open-source, self-hostable AI platform that wraps any LLM with enterprise-grade features: retrieval-augmented generation (RAG), deep research flows, custom agents, code execution, image generation, and voice mode. It connects to 50+ data sources via indexing connectors or MCP, making it a full internal AI stack rather than a chat wrapper. The platform recently shipped version 3.1.1 and has accumulated 24.8k GitHub stars. Unlike managed AI platforms, Onyx is self-deployed — teams can run it on Docker, Kubernetes, or Helm, and the Community Edition is entirely MIT licensed with no feature gating. Enterprise features like SSO, RBAC, and audit logging are available for teams that need them. What sets Onyx apart is the combination of depth and openness. Most open-source chat UIs are thin wrappers. Onyx ships agentic RAG that ranked on deep research leaderboards, plus an admin layer for managing connectors, access control, and usage analytics — all without sending data to a third-party cloud.
Reviewer scorecard
“The 1.0 stable tag finally gives us something to build on. The graph-based execution engine is exactly what I want for deterministic multi-step pipelines where I can't afford unpredictable LLM routing. Native MCP support means my existing tool ecosystem plugs straight in without adapter layers.”
“50+ connectors out of the box plus MCP support means you can actually index your entire company knowledge base without writing glue code. Self-hosting on Docker took about an hour to get running. This is what I wanted Danswer to become — and it did.”
“ADK's tight coupling to Vertex AI is a genuine lock-in concern. The 'production-ready' badge comes with an implicit 'on Google Cloud' qualifier. For teams running on AWS or Azure, the deployment story is clunky. LangGraph and CrewAI are more cloud-agnostic and have larger community ecosystems right now.”
“Self-hosting an enterprise AI platform is not trivial — you own the infra, the updates, the security patches, and the connector maintenance. For small teams without a dedicated DevOps person, the operational overhead will eat the productivity gains. The MIT license is genuinely free until you need the enterprise features, at which point the pricing is opaque.”
“Google going stable on a multi-language agent framework signals they're treating this as core infrastructure, not a demo. The Agent-to-Agent (A2A) protocol work alongside ADK hints at Google's real play: defining how agents communicate at internet scale, the same way HTTP defined how documents communicate.”
“The open-source enterprise AI stack is the play for companies that can't trust their proprietary data to third-party clouds — which is most regulated industries. Onyx is building the infrastructure layer for sovereign AI deployments, and 25k stars suggests the market agrees.”
“For no-code and low-code builders who want to graduate to real agent workflows, ADK's structured graph model is more approachable than writing raw LangChain chains. The TypeScript version in particular opens this to a much wider pool of front-end developers who want to add agentic features to their apps.”
“Deep research that actually cites your internal docs rather than hallucinating sources is genuinely useful for content teams. The voice mode and image generation being bundled in means one deployment covers most creative workflows.”
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