Comparison
databerry vs anything-llm
Verdict
Pick databerry if suitable for users looking to develop custom LLM agents without coding expertise; pick anything-llm if anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows.
Markdown twin · databerry alternatives · anything-llm alternatives
GraphCanon updated Sep 20, 2026
5views this month
vs
Trust & integrity
| Signal | databerry | anything-llm |
|---|---|---|
| Maintenance | Dormant (824d since push) As of Sep 20, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- databerry
- The no-code platform for building custom LLM Agents
- anything-llm
- Self-hosted AI agent experience
Stars
- databerry
- 3.0k
- anything-llm
- 66k
Forks
- databerry
- 415
- anything-llm
- 7.3k
Open issues
- databerry
- 166
- anything-llm
- 315
Language
- databerry
- -
- anything-llm
- JavaScript
Adopt for
- databerry
- Suitable for users looking to develop custom LLM agents without coding expertise.
- anything-llm
- anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows.
Persona
- databerry
- -
- anything-llm
- -
Runtime
- databerry
- -
- anything-llm
- -
License
- databerry
- -
- anything-llm
- MIT License, allowing for free use, modification, and distribution.
Last pushed
- databerry
- Jun 17, 2024
- anything-llm
- Sep 17, 2026
Categories
- databerry
- AI Agents, Developer Tools
- anything-llm
- AI Agents, Developer Tools, Inference & Serving
Trust and health
Maintenance
- databerry
- Dormant (18%)
- anything-llm
- Very active (96%)
Days since push
- databerry
- 824d
- anything-llm
- 0d
Open issues (now)
- databerry
- 166
- anything-llm
- 315
Stars delta
- databerry
- +1 (30d)
- anything-llm
- +1.5k (30d)
Open issues delta
- databerry
- 0 (30d)
- anything-llm
- -4 (30d)
Owner type
- databerry
- User
- anything-llm
- Organization
Full report
- databerry
- Trust report
- anything-llm
- Trust report
Choose databerry if…
- Tags unique to databerry: ai, aichatbot, chatbot, llm.
- When you have non-technical team members who need to craft and deploy specific AI chatbot functionalities.
- Leaner open-issue backlog (166).
When NOT to use databerry
- If you are a seasoned developer looking for customizable control over agent functions beyond no-code capabilities.
- In scenarios requiring integration with complex, non-standard APIs or systems that cannot be managed on a no-code platform.
Choose anything-llm if…
- Pricing: Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure..
- Requirements: Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment..
- Tags unique to anything-llm: agent-computer, agent-harness, agent-orchestration, agentic-ai.
- Also covers Inference & Serving.
- When you need a local-first AI agent experience that you can fully control and customize.
When NOT to use anything-llm
- If you require a cloud-based solution with minimal setup and maintenance, as anything-llm requires self-hosting and local management.
- When you need a platform that does not offer extensive deployment flexibility, as anything-llm provides multiple deployment options which might be overwhelming for users seeking simplicity.
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 Sep 20, 2026
- GitHub forks (gmpetrov/databerry) · observed Sep 20, 2026
- Last push (gmpetrov/databerry) · observed Jun 17, 2024
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Mintplex-Labs/anything-llm) · observed Sep 20, 2026
- GitHub forks (Mintplex-Labs/anything-llm) · observed Sep 20, 2026
- Last push (Mintplex-Labs/anything-llm) · observed Sep 17, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: databerry 3.0k · anything-llm 66k (synced Sep 20, 2026).
Common questions
- What is the difference between databerry and anything-llm?
- databerry: The no-code platform for building custom LLM Agents. anything-llm: Self-hosted AI agent experience. See the comparison table for live GitHub stats and shared categories.
- When should I choose databerry over anything-llm?
- Choose databerry over anything-llm when Tags unique to databerry: ai, aichatbot, chatbot, llm; When you have non-technical team members who need to craft and deploy specific AI chatbot functionalities; Leaner open-issue backlog (166).
- When should I choose anything-llm over databerry?
- Choose anything-llm over databerry when Pricing: Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure.; Requirements: Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment.; Tags unique to anything-llm: agent-computer, agent-harness, agent-orchestration, agentic-ai; Also covers Inference & Serving; When you need a local-first AI agent experience that you can fully control and customize.
- When should I avoid databerry?
- If you are a seasoned developer looking for customizable control over agent functions beyond no-code capabilities. In scenarios requiring integration with complex, non-standard APIs or systems that cannot be managed on a no-code platform.
- When should I avoid anything-llm?
- If you require a cloud-based solution with minimal setup and maintenance, as anything-llm requires self-hosting and local management. When you need a platform that does not offer extensive deployment flexibility, as anything-llm provides multiple deployment options which might be overwhelming for users seeking simplicity.
- Is databerry or anything-llm more popular on GitHub?
- anything-llm has more GitHub stars (66,167 vs 2,966). Stars measure visibility, not whether either tool fits your constraints.
- Are databerry and anything-llm open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to databerry or anything-llm?
- GraphCanon lists graph-backed alternatives at databerry alternatives and anything-llm alternatives (databerry markdown twin, anything-llm 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 anything-llm?
- databerry: Dormant. anything-llm: 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 anything-llm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: databerry trust report; anything-llm trust report.