--- title: "search vs bootcamp" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kelindar-search-vs-milvus-io-bootcamp" tools: ["kelindar-search", "milvus-io-bootcamp"] --- # search vs bootcamp *GraphCanon updated Aug 23, 2026* ## Verdict Pick search if search is a Go library enabling embedded vector search and semantic embeddings via the llama.cpp framework; pick bootcamp if interactive bootcamp for mastering Milvus use cases through tutorials and demos in areas like image search, audio search, molecular search, and more. [search](https://github.com/kelindar/search) reports 558 GitHub stars, 24 forks, and 5 open issues, last pushed Mar 6, 2026. [bootcamp](https://milvus.io) has 2.4k stars, 684 forks, and 0 open issues, last pushed Aug 11, 2026. Figures are from public GitHub metadata via [search's repository](https://github.com/kelindar/search) and [bootcamp's repository](https://github.com/milvus-io/bootcamp). | | [search](/tools/kelindar-search.md) | [bootcamp](/tools/milvus-io-bootcamp.md) | | --- | --- | --- | | Tagline | Go library for embedded vector search and semantic embeddings with llamacpp | Dealing with all unstructured data including reverse image search, audio search, molecular search, video analysis, and question-answer systems. | | Stars | 558 | 2,443 | | Forks | 24 | 684 | | Open issues | 5 | 0 | | Language | Go | Jupyter Notebook | | Adopt for | search is a Go library enabling embedded vector search and semantic embeddings via the llama.cpp framework. | Interactive bootcamp for mastering Milvus use cases through tutorials and demos in areas like image search, audio search, molecular search, and more. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | Computer Vision, Data & Retrieval, Evaluation & Observability, Speech & Audio, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [search](/tools/kelindar-search.md) | [bootcamp](/tools/milvus-io-bootcamp.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 169d | 10d | | Open issues (now) | 5 | 0 | | Stars delta | +3 (30d) | +4 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/kelindar-search/trust.md) | [trust report](/tools/milvus-io-bootcamp/trust.md) | ## Decision facts: search - **Adopt for:** search is a Go library enabling embedded vector search and semantic embeddings via the llama.cpp framework. ## Decision facts: bootcamp - **Adopt for:** Interactive bootcamp for mastering Milvus use cases through tutorials and demos in areas like image search, audio search, molecular search, and more. ## Choose when ### Choose search if… - search is primarily Go; bootcamp is Jupyter Notebook. - License: search is MIT, bootcamp is Apache-2.0. - Tags unique to search: ai, bert, gguf, gpu. - Use for projects needing a lightweight, fast integration of semantic search capabilities within applications written in Go ### Choose bootcamp if… - bootcamp is primarily Jupyter Notebook; search is Go. - License: bootcamp is Apache-2.0, search is MIT. - Tags unique to bootcamp: audio-search, deep-learning, image-classification, image-recognition. - Also covers Computer Vision, Evaluation & Observability, Speech & Audio. - - **When you need comprehensive integration guides**: Bootcamp offers detailed notebooks covering diverse use cases such as RAG, semantic search, hybrid searches, question answering systems, and video ## When NOT to use search - Avoid if relying on out-of-the-box support beyond Go or requiring heavy customization that is not supported directly by llama.cpp's capabilities - Not suitable when a more comprehensive database service with extensive querying and integration features is desired over an embedded solution ## When NOT to use bootcamp - - **When you want quick and minimal setup**: Bootcamp provides extensive integration possibilities but may require more setup effort compared to simpler tools, which could be a drawback if streamlined - operations are needed. - - **If focused on non-vector database solutions**: Since bootcamp is specific to Milvus and its wide array of vector search functionalities, it's less useful for those looking into other types of data - storage or processing that do not involve vector databases. ## Common questions ### What is the difference between search and bootcamp? search: Go library for embedded vector search and semantic embeddings with llamacpp. bootcamp: Dealing with all unstructured data including reverse image search, audio search, molecular search, video analysis, and question-answer systems.. See the comparison table for live GitHub stats and shared categories. ### When should I choose search over bootcamp? Choose search over bootcamp when search is primarily Go; bootcamp is Jupyter Notebook; License: search is MIT, bootcamp is Apache-2.0; Tags unique to search: ai, bert, gguf, gpu; Use for projects needing a lightweight, fast integration of semantic search capabilities within applications written in Go. ### When should I choose bootcamp over search? Choose bootcamp over search when bootcamp is primarily Jupyter Notebook; search is Go; License: bootcamp is Apache-2.0, search is MIT; Tags unique to bootcamp: audio-search, deep-learning, image-classification, image-recognition; Also covers Computer Vision, Evaluation & Observability, Speech & Audio; - **When you need comprehensive integration guides**: Bootcamp offers detailed notebooks covering diverse use cases such as RAG, semantic search, hybrid searches, question answering systems, and video. ### When should I avoid search? Avoid if relying on out-of-the-box support beyond Go or requiring heavy customization that is not supported directly by llama.cpp's capabilities Not suitable when a more comprehensive database service with extensive querying and integration features is desired over an embedded solution ### When should I avoid bootcamp? - **When you want quick and minimal setup**: Bootcamp provides extensive integration possibilities but may require more setup effort compared to simpler tools, which could be a drawback if streamlined operations are needed. - **If focused on non-vector database solutions**: Since bootcamp is specific to Milvus and its wide array of vector search functionalities, it's less useful for those looking into other types of data storage or processing that do not involve vector databases. ### Is search or bootcamp more popular on GitHub? bootcamp has more GitHub stars (2,443 vs 558). Stars measure visibility, not whether either tool fits your constraints. ### Are search and bootcamp open source? Yes - both are open-source projects on GitHub (search: MIT, bootcamp: Apache-2.0). ### Where can I find alternatives to search or bootcamp? GraphCanon lists graph-backed alternatives at [search alternatives](/tools/kelindar-search/alternatives) and [bootcamp alternatives](/tools/milvus-io-bootcamp/alternatives) ([search markdown twin](/tools/kelindar-search/alternatives.md), [bootcamp markdown twin](/tools/milvus-io-bootcamp/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/kelindar-search-vs-milvus-io-bootcamp.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, search or bootcamp? search: Slowing. bootcamp: 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 search and bootcamp? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [search trust report](/tools/kelindar-search/trust); [bootcamp trust report](/tools/milvus-io-bootcamp/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kelindar-search`](/api/graphcanon/graph?tool=kelindar-search) - 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/_