--- title: "databerry vs stackql" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/gmpetrov-databerry-vs-stackql-stackql" tools: ["gmpetrov-databerry", "stackql-stackql"] --- # databerry vs stackql *GraphCanon updated Aug 15, 2026* ## Verdict Pick databerry if suitable for users looking to develop custom LLM agents without coding expertise; pick stackql if stackQL is a SQL-based framework that allows users to query and manage various cloud resources using familiar SQL commands. [databerry](https://chaindesk.ai) reports 3.0k GitHub stars, 420 forks, and 166 open issues, last pushed Jun 17, 2024. [stackql](https://stackql.io/) has 862 stars, 80 forks, and 103 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [databerry's repository](https://github.com/gmpetrov/databerry) and [stackql's repository](https://github.com/stackql/stackql). | | [databerry](/tools/gmpetrov-databerry.md) | [stackql](/tools/stackql-stackql.md) | | --- | --- | --- | | Tagline | The no-code platform for building custom LLM Agents | Unified SQL-based framework for querying and managing resources | | Stars | 2,965 | 862 | | Forks | 420 | 80 | | Open issues | 166 | 103 | | Language | - | Go | | Adopt for | Suitable for users looking to develop custom LLM agents without coding expertise. | StackQL is a SQL-based framework that allows users to query and manage various cloud resources using familiar SQL commands. | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [databerry](/tools/gmpetrov-databerry.md) | [stackql](/tools/stackql-stackql.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 788d | 0d | | Open issues (now) | 166 | 103 | | Stars delta | +4 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/gmpetrov-databerry/trust.md) | [trust report](/tools/stackql-stackql/trust.md) | ## Decision facts: databerry - **Adopt for:** Suitable for users looking to develop custom LLM agents without coding expertise. ## Decision facts: stackql - **Adopt for:** StackQL is a SQL-based framework that allows users to query and manage various cloud resources using familiar SQL commands. ## Choose when ### 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. - More GitHub stars (3.0k vs 862) - visibility, not fit. ### Choose stackql if… - Tags unique to stackql: cloud-automation, cloud-config, infrastructure-as-code, llm-tools. - stackql ships Docker support for self-hosted deployment. - - When you need to work across multiple cloud providers and SaaS platforms and desire consistency in resource management through SQL queries ## 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. ## When NOT to use stackql - - If your environment strictly enforces language-specific tools and you are already heavily invested in a toolset built outside of Go - - In scenarios where SQL-based querying does not align with the team's workflow or expertise, preferring more direct API-style interactions instead ## Common questions ### What is the difference between databerry and stackql? databerry: The no-code platform for building custom LLM Agents. stackql: Unified SQL-based framework for querying and managing resources. See the comparison table for live GitHub stats and shared categories. ### When should I choose databerry over stackql? Choose databerry over stackql 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; More GitHub stars (3.0k vs 862) - visibility, not fit. ### When should I choose stackql over databerry? Choose stackql over databerry when Tags unique to stackql: cloud-automation, cloud-config, infrastructure-as-code, llm-tools; stackql ships Docker support for self-hosted deployment; - When you need to work across multiple cloud providers and SaaS platforms and desire consistency in resource management through SQL queries. ### 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 stackql? - If your environment strictly enforces language-specific tools and you are already heavily invested in a toolset built outside of Go - In scenarios where SQL-based querying does not align with the team's workflow or expertise, preferring more direct API-style interactions instead ### Is databerry or stackql more popular on GitHub? databerry has more GitHub stars (2,965 vs 862). Stars measure visibility, not whether either tool fits your constraints. ### Are databerry and stackql open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to databerry or stackql? GraphCanon lists graph-backed alternatives at [databerry alternatives](/tools/gmpetrov-databerry/alternatives) and [stackql alternatives](/tools/stackql-stackql/alternatives) ([databerry markdown twin](/tools/gmpetrov-databerry/alternatives.md), [stackql markdown twin](/tools/stackql-stackql/alternatives.md)), 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](/compare/gmpetrov-databerry-vs-stackql-stackql.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, databerry or stackql? databerry: Dormant. stackql: 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 stackql? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [databerry trust report](/tools/gmpetrov-databerry/trust); [stackql trust report](/tools/stackql-stackql/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=gmpetrov-databerry`](/api/graphcanon/graph?tool=gmpetrov-databerry) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_