--- title: "embedbase vs dingo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/different-ai-embedbase-vs-dingodb-dingo" tools: ["different-ai-embedbase", "dingodb-dingo"] --- # embedbase vs dingo *GraphCanon updated Aug 21, 2026* ## Verdict Pick embedbase if embedbase is a TypeScript-based API designed to facilitate the creation of Large Language Model (LLM) powered applications via integrations with embeddings and vector databases; pick dingo if dingoDB is a MySQL-compatible database designed for handling both structured and unstructured data with support for real-time semantic search. [embedbase](https://docs.embedbase.xyz) reports 524 GitHub stars, 55 forks, and 35 open issues, last pushed Nov 27, 2024. [dingo](https://www.dingodb.com) has 1.7k stars, 265 forks, and 8 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [embedbase's repository](https://github.com/different-ai/embedbase) and [dingo's repository](https://github.com/dingodb/dingo). | | [embedbase](/tools/different-ai-embedbase.md) | [dingo](/tools/dingodb-dingo.md) | | --- | --- | --- | | Tagline | A dead-simple API to build LLM-powered apps | A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data | | Stars | 524 | 1,701 | | Forks | 55 | 265 | | Open issues | 35 | 8 | | Language | TypeScript | Java | | Adopt for | Embedbase is a TypeScript-based API designed to facilitate the creation of Large Language Model (LLM) powered applications via integrations with embeddings and vector databases. | DingoDB is a MySQL-compatible database designed for handling both structured and unstructured data with support for real-time semantic search. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [embedbase](/tools/different-ai-embedbase.md) | [dingo](/tools/dingodb-dingo.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 601d | 42d | | Open issues (now) | 35 | 8 | | Stars delta | Unknown | +2 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/different-ai-embedbase/trust.md) | [trust report](/tools/dingodb-dingo/trust.md) | ## Decision facts: embedbase - **Adopt for:** Embedbase is a TypeScript-based API designed to facilitate the creation of Large Language Model (LLM) powered applications via integrations with embeddings and vector databases. ## Decision facts: dingo - **Adopt for:** DingoDB is a MySQL-compatible database designed for handling both structured and unstructured data with support for real-time semantic search. ## Choose when ### Choose embedbase if… - embedbase is primarily TypeScript; dingo is Java. - License: embedbase is MIT, dingo is Apache-2.0. - Tags unique to embedbase: ai, artificial-intelligence, chatgpt, embeddings. - * Use Embedbase if you require direct integration capabilities specifically designed for embeddings and vector databases, like pgvector or Supabase. ### Choose dingo if… - dingo is primarily Java; embedbase is TypeScript. - License: dingo is Apache-2.0, embedbase is MIT. - Tags unique to dingo: embedding-search, embedding-store, hybrid-search, key-value-distributed-store. - You need a unified SQL interface for vector queries on diverse data types ## When NOT to use embedbase - * Avoid using Embedbase if your application's technology stack cannot effectively integrate TypeScript, as its primary language support is in this framework and not others like Python. - * Do not use it when you need extensive customization options for the vector database configurations beyond what pgvector or Supabase offers. ## When NOT to use dingo - If your application strictly demands non-SQL interfaces for querying - When the Apache-2.0 license is incompatible with your project requirements ## Common questions ### What is the difference between embedbase and dingo? embedbase: A dead-simple API to build LLM-powered apps. dingo: A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data. See the comparison table for live GitHub stats and shared categories. ### When should I choose embedbase over dingo? Choose embedbase over dingo when embedbase is primarily TypeScript; dingo is Java; License: embedbase is MIT, dingo is Apache-2.0; Tags unique to embedbase: ai, artificial-intelligence, chatgpt, embeddings; * Use Embedbase if you require direct integration capabilities specifically designed for embeddings and vector databases, like pgvector or Supabase. ### When should I choose dingo over embedbase? Choose dingo over embedbase when dingo is primarily Java; embedbase is TypeScript; License: dingo is Apache-2.0, embedbase is MIT; Tags unique to dingo: embedding-search, embedding-store, hybrid-search, key-value-distributed-store; You need a unified SQL interface for vector queries on diverse data types. ### When should I avoid embedbase? * Avoid using Embedbase if your application's technology stack cannot effectively integrate TypeScript, as its primary language support is in this framework and not others like Python. * Do not use it when you need extensive customization options for the vector database configurations beyond what pgvector or Supabase offers. ### When should I avoid dingo? If your application strictly demands non-SQL interfaces for querying When the Apache-2.0 license is incompatible with your project requirements ### Is embedbase or dingo more popular on GitHub? dingo has more GitHub stars (1,701 vs 524). Stars measure visibility, not whether either tool fits your constraints. ### Are embedbase and dingo open source? Yes - both are open-source projects on GitHub (embedbase: MIT, dingo: Apache-2.0). ### Where can I find alternatives to embedbase or dingo? GraphCanon lists graph-backed alternatives at [embedbase alternatives](/tools/different-ai-embedbase/alternatives) and [dingo alternatives](/tools/dingodb-dingo/alternatives) ([embedbase markdown twin](/tools/different-ai-embedbase/alternatives.md), [dingo markdown twin](/tools/dingodb-dingo/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/different-ai-embedbase-vs-dingodb-dingo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, embedbase or dingo? embedbase: Dormant. dingo: Steady. 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 embedbase and dingo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [embedbase trust report](/tools/different-ai-embedbase/trust); [dingo trust report](/tools/dingodb-dingo/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=different-ai-embedbase`](/api/graphcanon/graph?tool=different-ai-embedbase) - 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/_