Google Agent Development Kit (ADK) vs Databricks Mosaic AI Agent Framework
Detailed side-by-side comparison to help you choose the right tool
Google Agent Development Kit (ADK)
🔴DeveloperAI Agent Frameworks
Google's open-source, code-first framework for building, evaluating, and deploying AI agents. Optimized for Gemini but works with any LLM.
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ContactDatabricks Mosaic AI Agent Framework
AI Agent Frameworks
Enterprise AI agent framework built into the Databricks Lakehouse, with MLOps, evaluation tooling, governance, and MCP support for building production agents on proprietary data.
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Google Agent Development Kit (ADK) - Pros & Cons
Pros
- ✓Completely free and open-source
- ✓Model-agnostic despite Google origins
- ✓Strong Gemini optimization
- ✓Built-in evaluation framework
- ✓Backed by Google's engineering team
- ✓Clean Python-first API
- ✓Integrates with Vertex AI for production
Cons
- ✗Requires Python programming knowledge
- ✗Newer framework with smaller community than LangChain
- ✗Documentation still maturing
- ✗Best features tied to Google ecosystem
- ✗Steeper learning curve than no-code alternatives
- ✗Limited third-party integrations compared to competitors
Databricks Mosaic AI Agent Framework - Pros & Cons
Pros
- ✓Agents query Lakehouse tables and Unity Catalog assets directly, no ETL required
- ✓Agent Evaluation suite combines automated checks and human review in one workflow
- ✓MCP support in both directions connects agents to the broader tool ecosystem
- ✓AI Gateway provides centralized cost tracking, rate limiting, and model routing
- ✓Governance is built in, not bolted on: lineage, access control, and audit trails come standard
- ✓Model-agnostic: use Databricks-hosted models, OpenAI, Anthropic, or open-source models through the same framework
Cons
- ✗Requires an existing Databricks platform investment, creating significant vendor lock-in
- ✗DBU-based pricing is difficult to predict without modeling expected query volumes
- ✗Steep learning curve for teams not already familiar with the Databricks ecosystem
- ✗No free tier or self-serve trial for agent-specific features
- ✗Serverless SQL costs ($0.70/DBU) can escalate quickly for analytics-heavy agent workloads
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