--- title: "aquila vs cuvs" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aquila-network-aquila-vs-nvidia-cuvs" tools: ["aquila-network-aquila", "nvidia-cuvs"] --- # aquila vs cuvs *GraphCanon updated Aug 23, 2026* ## Verdict Pick aquila if aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches; pick cuvs if cuVS is a CUDA-based library for efficient GPU-accelerated vector search and clustering. [aquila](https://aquila.network) reports 379 GitHub stars, 26 forks, and 13 open issues, last pushed May 6, 2024. [cuvs](https://docs.rapids.ai/api/cuvs/stable/) has 838 stars, 223 forks, and 692 open issues, last pushed Aug 22, 2026. Figures are from public GitHub metadata via [aquila's repository](https://github.com/Aquila-Network/aquila) and [cuvs's repository](https://github.com/NVIDIA/cuvs). | | [aquila](/tools/aquila-network-aquila.md) | [cuvs](/tools/nvidia-cuvs.md) | | --- | --- | --- | | Tagline | Efficient Neural Search Engine | A library for vector search and clustering on the GPU | | Stars | 379 | 838 | | Forks | 26 | 223 | | Open issues | 13 | 692 | | Language | HTML | Cuda | | Adopt for | Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches. | cuVS is a CUDA-based library for efficient GPU-accelerated vector search and clustering. | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aquila](/tools/aquila-network-aquila.md) | [cuvs](/tools/nvidia-cuvs.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 817d | 1d | | Open issues (now) | 13 | 692 | | Stars delta | Unknown | +17 (30d) | | Open issues delta | Unknown | +47 (30d) | | Full report | [trust report](/tools/aquila-network-aquila/trust.md) | [trust report](/tools/nvidia-cuvs/trust.md) | ## Decision facts: aquila - **Adopt for:** Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches. ## Decision facts: cuvs - **Adopt for:** cuVS is a CUDA-based library for efficient GPU-accelerated vector search and clustering. ## Choose when ### Choose aquila if… - aquila is primarily HTML; cuvs is Cuda. - Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors. - Also covers Data & Retrieval. - When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary ### Choose cuvs if… - cuvs is primarily Cuda; aquila is HTML. - Tags unique to cuvs: anns, clustering, cuda, gpu. - cuvs ships Docker support for self-hosted deployment. - - When you need high-performance vector operations leveraging the parallel processing power of GPUs, specifically with CUDA. ## When NOT to use aquila - If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration - In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide ## When NOT to use cuvs - - For environments where GPU resources are limited or unavailable because cuVS heavily relies on CUDA's capabilities for performance gains. - - When you prioritize portability across different hardware, as cuVS being tied to CUDA means it may not be optimal on non-NVIDIA GPUs or CPU-only systems. ## Common questions ### What is the difference between aquila and cuvs? aquila: Efficient Neural Search Engine. cuvs: A library for vector search and clustering on the GPU. See the comparison table for live GitHub stats and shared categories. ### When should I choose aquila over cuvs? Choose aquila over cuvs when aquila is primarily HTML; cuvs is Cuda; Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors; Also covers Data & Retrieval; When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary. ### When should I choose cuvs over aquila? Choose cuvs over aquila when cuvs is primarily Cuda; aquila is HTML; Tags unique to cuvs: anns, clustering, cuda, gpu; cuvs ships Docker support for self-hosted deployment; - When you need high-performance vector operations leveraging the parallel processing power of GPUs, specifically with CUDA. ### When should I avoid aquila? If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide ### When should I avoid cuvs? - For environments where GPU resources are limited or unavailable because cuVS heavily relies on CUDA's capabilities for performance gains. - When you prioritize portability across different hardware, as cuVS being tied to CUDA means it may not be optimal on non-NVIDIA GPUs or CPU-only systems. ### Is aquila or cuvs more popular on GitHub? cuvs has more GitHub stars (838 vs 379). Stars measure visibility, not whether either tool fits your constraints. ### Are aquila and cuvs open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to aquila or cuvs? GraphCanon lists graph-backed alternatives at [aquila alternatives](/tools/aquila-network-aquila/alternatives) and [cuvs alternatives](/tools/nvidia-cuvs/alternatives) ([aquila markdown twin](/tools/aquila-network-aquila/alternatives.md), [cuvs markdown twin](/tools/nvidia-cuvs/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/aquila-network-aquila-vs-nvidia-cuvs.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aquila or cuvs? aquila: Dormant. cuvs: 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 aquila and cuvs? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aquila trust report](/tools/aquila-network-aquila/trust); [cuvs trust report](/tools/nvidia-cuvs/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aquila-network-aquila`](/api/graphcanon/graph?tool=aquila-network-aquila) - 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/_