--- title: "dingo vs milvus" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dingodb-dingo-vs-milvus-io-milvus" tools: ["dingodb-dingo", "milvus-io-milvus"] --- # dingo vs milvus Neutral, constraint-first comparison with live GitHub stats. | | [dingo](/tools/dingodb-dingo.md) | [milvus](/tools/milvus-io-milvus.md) | | --- | --- | --- | | Tagline | A multi-modal vector database that supports upserts and vector queries using unified SQL on structured and unstructured data | High-performance cloud-native vector database for scalable vector ANN search | | Stars | 1,701 | 45,133 | | Forks | 264 | 4,109 | | Open issues | 8 | 972 | | Language | Java | Go | | Adopt for | Dingo is a multi-modal vector database adept at serving both structured and unstructured data, featuring MySQL compatibility, high concurrency, low latency, and real-time scalar-vector hybrid retrieval. It supports SQL,悠 | Milvus is a high-performance vector database built for scalable vector ANN search, designed for handling vast amounts of unstructured data such as text and images. It offers a fully distributed and Kubernetes-native (K8s | | Persona | - | - | | Runtime | - | - | | License | Dingo is licensed under Apache-2.0 | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dingo](/tools/dingodb-dingo.md) | [milvus](/tools/milvus-io-milvus.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 43d | 0d | | Open issues (now) | 8 | 972 | | Security scan | Not scanned | 12 low (12 low) | | Full report | [trust report](/tools/dingodb-dingo/trust.md) | [trust report](/tools/milvus-io-milvus/trust.md) | **Typed relationship:** dingo _(alternative)_ milvus DingoDB and Milvus are both high-performance vector databases, providing similarity search capabilities for large-scale datasets. DingoDB differentiates itself with support for MySQL-compatible SQL queries. ## Decision facts: dingo - **Requirements:** Min 8 GB RAM; Requires Docker - **Adopt for:** Dingo is a multi-modal vector database adept at serving both structured and unstructured data, featuring MySQL compatibility, high concurrency, low latency, and real-time scalar-vector hybrid retrieval. It supports SQL,悠 - **License detail:** Dingo is licensed under Apache-2.0 ## Decision facts: milvus - **Adopt for:** Milvus is a high-performance vector database built for scalable vector ANN search, designed for handling vast amounts of unstructured data such as text and images. It offers a fully distributed and Kubernetes-native (K8s ## Choose when ### Choose dingo if… - dingo is primarily Java; milvus is Go. - Requirements: Min 8 GB RAM; Requires Docker. - DingoDB and Milvus are both high-performance vector databases, providing similarity search capabilities for large-scale datasets. DingoDB differentiates itself with support for MySQL-compatible SQL queries. - Tags unique to dingo: key-value-distributed-store, unified-sql, real-time-semantic-search, embedding-search. - Also covers Data & Retrieval. - - When you require efficient handling of mixed structured and unstructured data within an enterprise-grade solution with high availability. ### Choose milvus if… - milvus is primarily Go; dingo is Java. - DingoDB and Milvus are both high-performance vector databases, providing similarity search capabilities for large-scale datasets. DingoDB differentiates itself with support for MySQL-compatible SQL queries. - Tags unique to milvus: anns, distributed, cloud-native, embedding-database. - milvus ships Docker support for self-hosted deployment. - You need to perform near real-time similarity searches on large-scale datasets with efficient search performance. ## When NOT to use dingo - - If you are looking for a solution that does not offer MySQL compatibility or SQL support for vector databases. - - When your application’s requirements do not include hybrid scalar-vector retrievals and real-time index optimization capabilities. - - If your project specifically excludes Java-based solutions or does not benefit from the automatic elastic sharding Dingo provides. ## When NOT to use milvus - Your project requires extensive SQL-like querying capabilities, as Milvus specializes in vector data management rather than traditional relational data handling. - If you require a fully managed service with minimal setup overhead, consider alternatives or use Zilliz Cloud for the managed version of Milvus. The standalone and distributed versions may demand more - You are working on small-scale projects where simplicity outweighs performance and scalability needs, since Milvus is designed for high-performance and scale which might be excessive. ## Common questions ### What is the difference between dingo and milvus? dingo: A multi-modal vector database that supports upserts and vector queries using unified SQL on structured and unstructured data. milvus: High-performance cloud-native vector database for scalable vector ANN search. See the comparison table for live GitHub stats and shared categories. ### When should I choose dingo over milvus? Choose dingo over milvus when dingo is primarily Java; milvus is Go; Requirements: Min 8 GB RAM; Requires Docker; DingoDB and Milvus are both high-performance vector databases, providing similarity search capabilities for large-scale datasets. DingoDB differentiates itself with support for MySQL-compatible SQL queries; Tags unique to dingo: key-value-distributed-store, unified-sql, real-time-semantic-search, embedding-search; Also covers Data & Retrieval; - When you require efficient handling of mixed structured and unstructured data within an enterprise-grade solution with high availability. ### When should I choose milvus over dingo? Choose milvus over dingo when milvus is primarily Go; dingo is Java; DingoDB and Milvus are both high-performance vector databases, providing similarity search capabilities for large-scale datasets. DingoDB differentiates itself with support for MySQL-compatible SQL queries; Tags unique to milvus: anns, distributed, cloud-native, embedding-database; milvus ships Docker support for self-hosted deployment; You need to perform near real-time similarity searches on large-scale datasets with efficient search performance. ### When should I avoid dingo? - If you are looking for a solution that does not offer MySQL compatibility or SQL support for vector databases. - When your application’s requirements do not include hybrid scalar-vector retrievals and real-time index optimization capabilities. - If your project specifically excludes Java-based solutions or does not benefit from the automatic elastic sharding Dingo provides. ### When should I avoid milvus? Your project requires extensive SQL-like querying capabilities, as Milvus specializes in vector data management rather than traditional relational data handling. If you require a fully managed service with minimal setup overhead, consider alternatives or use Zilliz Cloud for the managed version of Milvus. The standalone and distributed versions may demand more You are working on small-scale projects where simplicity outweighs performance and scalability needs, since Milvus is designed for high-performance and scale which might be excessive. ### Is dingo or milvus more popular on GitHub? milvus has more GitHub stars (45,133 vs 1,701). Stars measure visibility, not whether either tool fits your constraints. ### Are dingo and milvus open source? Yes - both are open-source projects on GitHub (dingo: Apache-2.0, milvus: Apache-2.0). ### Where can I find alternatives to dingo or milvus? GraphCanon lists graph-backed alternatives at /tools/dingodb-dingo/alternatives and /tools/milvus-io-milvus/alternatives (/tools/dingodb-dingo/alternatives.md, /tools/milvus-io-milvus/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 /compare/dingodb-dingo-vs-milvus-io-milvus.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dingo or milvus? dingo: Steady. milvus: 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 dingo and milvus? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dingo: /tools/dingodb-dingo/trust; milvus: /tools/milvus-io-milvus/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dingodb-dingo`](/api/graphcanon/graph?tool=dingodb-dingo) - 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/_