--- title: "infinispan vs qdrant" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/infinispan-infinispan-vs-qdrant-qdrant" tools: ["infinispan-infinispan", "qdrant-qdrant"] --- # infinispan vs qdrant Neutral, constraint-first comparison with live GitHub stats. | | [infinispan](/tools/infinispan-infinispan.md) | [qdrant](/tools/qdrant-qdrant.md) | | --- | --- | --- | | Tagline | In-Memory Distributed Database | High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. | | Stars | 1,338 | 33,026 | | Forks | 653 | 2,466 | | Open issues | 444 | 621 | | Language | Java | Rust | | Adopt for | Infinispan is an open-source, distributed in-memory database that offers both caching and persistent storage solutions, making it a versatile choice for a variety of data management scenarios. | Qdrant is a high-performance, massive-scale vector database and search engine that leverages Rust for its performance under heavy loads. It supports extended filtering capabilities which make it suitable for neural-net,语 | | Persona | - | - | | Runtime | - | - | | License | 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._ | | [infinispan](/tools/infinispan-infinispan.md) | [qdrant](/tools/qdrant-qdrant.md) | | --- | --- | --- | | Open issues (now) | 444 | 621 | | Security scan | Not scanned | No lockfile | | Full report | [trust report](/tools/infinispan-infinispan/trust.md) | [trust report](/tools/qdrant-qdrant/trust.md) | **Typed relationship:** infinispan _(alternative)_ qdrant Infinispan and Qdrant both offer cloud-native vector storage capabilities, allowing them to serve as data stores for AI applications. However, they approach the problem differently with Infinispan focusing more on distributed in-memory data grids while Qdrant is optimized for vector similarity search. ## Decision facts: infinispan - **Pricing:** freemium - Infinispan operates under the Apache-2.0 open-source license making its core functionalities freely available. However, for enterprise support and additional plugins, users might need commercial plans - **Requirements:** Min 1 GB RAM; The minimum RAM depends on the application's memory usage; since Infinispan operates entirely in-memory, adequate system RAM is necessary to accommodate your in; For large-scale deployments or datasets that exceed typical server RAM sizes, careful planning and architecture design are required. - **Adopt for:** Infinispan is an open-source, distributed in-memory database that offers both caching and persistent storage solutions, making it a versatile choice for a variety of data management scenarios. ## Decision facts: qdrant - **Adopt for:** Qdrant is a high-performance, massive-scale vector database and search engine that leverages Rust for its performance under heavy loads. It supports extended filtering capabilities which make it suitable for neural-net,语 ## Choose when ### Choose infinispan if… - infinispan is primarily Java; qdrant is Rust. - Pricing: Infinispan operates under the Apache-2.0 open-source license making its core functionalities freely available. However, for enterprise support and additional plugins, users might need commercial plans. - Requirements: Min 1 GB RAM; The minimum RAM depends on the application's memory usage; since Infinispan operates entirely in-memory, adequate system RAM is necessary to accommodate your in; For large-scale deployments or datasets that exceed typical server RAM sizes, careful planning and architecture design are required.. - Infinispan and Qdrant both offer cloud-native vector storage capabilities, allowing them to serve as data stores for AI applications. However, they approach the problem differently with Infinispan focusing more on distributed in-memory data grids while Qdrant is optimized for vector similarity search. - Tags unique to infinispan: nosql, datagrid, persistent-storage, semantic-search. - Also covers Data & Retrieval. - Infinispan should be used when there's a need for high-speed data access where persistence isn't the primary concern but performance is critical. ### Choose qdrant if… - qdrant is primarily Rust; infinispan is Java. - Infinispan and Qdrant both offer cloud-native vector storage capabilities, allowing them to serve as data stores for AI applications. However, they approach the problem differently with Infinispan focusing more on distributed in-memory data grids while Qdrant is optimized for vector similarity search. - Tags unique to qdrant: knn-algorithm, embeddings-similarity, machine-learning, ai-search. - qdrant ships Docker support for self-hosted deployment. - When you need high performance and reliability under heavy load due to Qdrant's Rust-based implementation. ## When NOT to use infinispan - Avoid using Infinispan if your application strictly requires on-disk persistence for every operation; while it does offer persistent storage options, its strength lies more in its caching and in-memor - In situations where the amount of data is so vast that it won't fit into memory, or costs associated with scaling up memory resources are a concern, Infinispan may not be an optimal choice. ## When NOT to use qdrant - Avoid using Qdrant when the primary requirement is to interact with traditional relational databases rather than vector embeddings. - Do not choose Qdrant if your project does not require or benefit from faceted search capabilities, extended filtering support, or next-generation AI functionalities. - If you prefer open-source solutions with community-driven development and less reliance on managed cloud services. ## Common questions ### What is the difference between infinispan and qdrant? infinispan: In-Memory Distributed Database. qdrant: High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI.. See the comparison table for live GitHub stats and shared categories. ### When should I choose infinispan over qdrant? Choose infinispan over qdrant when infinispan is primarily Java; qdrant is Rust; Pricing: Infinispan operates under the Apache-2.0 open-source license making its core functionalities freely available. However, for enterprise support and additional plugins, users might need commercial plans; Requirements: Min 1 GB RAM; The minimum RAM depends on the application's memory usage; since Infinispan operates entirely in-memory, adequate system RAM is necessary to accommodate your in; For large-scale deployments or datasets that exceed typical server RAM sizes, careful planning and architecture design are required.; Infinispan and Qdrant both offer cloud-native vector storage capabilities, allowing them to serve as data stores for AI applications. However, they approach the problem differently with Infinispan focusing more on distributed in-memory data grids while Qdrant is optimized for vector similarity search; Tags unique to infinispan: nosql, datagrid, persistent-storage, semantic-search; Also covers Data & Retrieval; Infinispan should be used when there's a need for high-speed data access where persistence isn't the primary concern but performance is critical. ### When should I choose qdrant over infinispan? Choose qdrant over infinispan when qdrant is primarily Rust; infinispan is Java; Infinispan and Qdrant both offer cloud-native vector storage capabilities, allowing them to serve as data stores for AI applications. However, they approach the problem differently with Infinispan focusing more on distributed in-memory data grids while Qdrant is optimized for vector similarity search; Tags unique to qdrant: knn-algorithm, embeddings-similarity, machine-learning, ai-search; qdrant ships Docker support for self-hosted deployment; When you need high performance and reliability under heavy load due to Qdrant's Rust-based implementation. ### When should I avoid infinispan? Avoid using Infinispan if your application strictly requires on-disk persistence for every operation; while it does offer persistent storage options, its strength lies more in its caching and in-memor In situations where the amount of data is so vast that it won't fit into memory, or costs associated with scaling up memory resources are a concern, Infinispan may not be an optimal choice. ### When should I avoid qdrant? Avoid using Qdrant when the primary requirement is to interact with traditional relational databases rather than vector embeddings. Do not choose Qdrant if your project does not require or benefit from faceted search capabilities, extended filtering support, or next-generation AI functionalities. If you prefer open-source solutions with community-driven development and less reliance on managed cloud services. ### Is infinispan or qdrant more popular on GitHub? qdrant has more GitHub stars (33,026 vs 1,338). Stars measure visibility, not whether either tool fits your constraints. ### Are infinispan and qdrant open source? Yes - both are open-source projects on GitHub (infinispan: Apache-2.0, qdrant: Apache-2.0). ### Where can I find alternatives to infinispan or qdrant? GraphCanon lists graph-backed alternatives at /tools/infinispan-infinispan/alternatives and /tools/qdrant-qdrant/alternatives (/tools/infinispan-infinispan/alternatives.md, /tools/qdrant-qdrant/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/infinispan-infinispan-vs-qdrant-qdrant.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, infinispan or qdrant? infinispan: Very active. qdrant: 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 infinispan and qdrant? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: infinispan: /tools/infinispan-infinispan/trust; qdrant: /tools/qdrant-qdrant/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=infinispan-infinispan`](/api/graphcanon/graph?tool=infinispan-infinispan) - 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/_