Comparison
databerry vs agent-starter-pack
Verdict
Pick databerry when tags unique to databerry: ai, aichatbot, chatbot, chatbots; pick agent-starter-pack when requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks..
Markdown twin · databerry alternatives · agent-starter-pack alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | databerry | agent-starter-pack |
|---|---|---|
| Maintenance | Dormant (753d since push) As of 1d · github_public_v1 | Very active (0d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1d · github_public_v1 | Not a fork · Organization account As of 1d · github_public_v1 |
| Security (OSV) | No lockfile As of 1d · none | No lockfile As of 1d · none |
Tagline
- databerry
- The no-code platform for building custom LLM Agents
- agent-starter-pack
- Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.
Stars
- databerry
- 3.0k
- agent-starter-pack
- 6.5k
Forks
- databerry
- 422
- agent-starter-pack
- 1.5k
Open issues
- databerry
- 166
- agent-starter-pack
- 48
Language
- databerry
- -
- agent-starter-pack
- Python
Adopt for
- databerry
- -
- agent-starter-pack
- agent-starter-pack is a specialized toolset for deploying AI agents on the Google Cloud Platform with built-in CI/CD, evaluation tools, and observability features.
Persona
- databerry
- -
- agent-starter-pack
- -
Runtime
- databerry
- -
- agent-starter-pack
- -
License
- databerry
- -
- agent-starter-pack
- Apache-2.0
Last pushed
- databerry
- Jun 17, 2024
- agent-starter-pack
- Jul 10, 2026
Categories
- databerry
- AI Agents, LLM Frameworks
- agent-starter-pack
- AI Agents, Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- databerry
- Dormant (18%)
- agent-starter-pack
- Very active (96%)
Days since push
- databerry
- 753d
- agent-starter-pack
- 0d
Open issues (now)
- databerry
- 166
- agent-starter-pack
- 48
Owner type
- databerry
- User
- agent-starter-pack
- Organization
Full report
- databerry
- Trust report
- agent-starter-pack
- Trust report
Choose databerry if…
- Tags unique to databerry: ai, aichatbot, chatbot, chatbots.
When NOT to use databerry
- Last GitHub push was 754 days ago (dormant maintenance, Jun 17, 2024). Validate activity before betting a new project on databerry.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Choose agent-starter-pack if…
- Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks..
- Tags unique to agent-starter-pack: agents, gcp, gemini, genai-agents.
- Also covers Inference & Serving.
- When you require production-ready templates specifically adapted for deployment to Google Cloud.
When NOT to use agent-starter-pack
- If you are using another cloud provider (e.g., AWS, Azure) and do not plan on moving your operations to Google Cloud.
- When your team lacks familiarity with Python 3.10+ or does not wish to install and manage dependencies such as the Google Cloud SDK locally.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (gmpetrov/databerry) · observed Jul 11, 2026
- GitHub forks (gmpetrov/databerry) · observed Jul 11, 2026
- Last push (gmpetrov/databerry) · observed Jun 17, 2024
- License file (unknown) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (GoogleCloudPlatform/agent-starter-pack) · observed Jul 11, 2026
- GitHub forks (GoogleCloudPlatform/agent-starter-pack) · observed Jul 11, 2026
- Last push (GoogleCloudPlatform/agent-starter-pack) · observed Jul 10, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: databerry 3.0k · agent-starter-pack 6.5k (synced Jul 11, 2026).
Common questions
- What is the difference between databerry and agent-starter-pack?
- databerry: The no-code platform for building custom LLM Agents. agent-starter-pack: Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.. See the comparison table for live GitHub stats and shared categories.
- When should I choose databerry over agent-starter-pack?
- Choose databerry over agent-starter-pack when Tags unique to databerry: ai, aichatbot, chatbot, chatbots.
- When should I choose agent-starter-pack over databerry?
- Choose agent-starter-pack over databerry when Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks.; Tags unique to agent-starter-pack: agents, gcp, gemini, genai-agents; Also covers Inference & Serving; When you require production-ready templates specifically adapted for deployment to Google Cloud.
- When should I avoid databerry?
- Last GitHub push was 754 days ago (dormant maintenance, Jun 17, 2024). Validate activity before betting a new project on databerry. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- When should I avoid agent-starter-pack?
- If you are using another cloud provider (e.g., AWS, Azure) and do not plan on moving your operations to Google Cloud. When your team lacks familiarity with Python 3.10+ or does not wish to install and manage dependencies such as the Google Cloud SDK locally.
- Is databerry or agent-starter-pack more popular on GitHub?
- agent-starter-pack has more GitHub stars (6,514 vs 2,960). Stars measure visibility, not whether either tool fits your constraints.
- Are databerry and agent-starter-pack open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to databerry or agent-starter-pack?
- GraphCanon lists graph-backed alternatives at databerry alternatives and agent-starter-pack alternatives (databerry markdown twin, agent-starter-pack markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, databerry or agent-starter-pack?
- databerry: Dormant. agent-starter-pack: Very active. 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 databerry and agent-starter-pack?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: databerry trust report; agent-starter-pack trust report.