--- title: "arcadedb vs weaviate" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arcadedata-arcadedb-vs-weaviate-weaviate" tools: ["arcadedata-arcadedb", "weaviate-weaviate"] --- # arcadedb vs weaviate Neutral, constraint-first comparison with live GitHub stats. | | [arcadedb](/tools/arcadedata-arcadedb.md) | [weaviate](/tools/weaviate-weaviate.md) | | --- | --- | --- | | Tagline | Multi Model DBMS Built for Extreme Performance | Open-source vector database for scalable semantic search | | Stars | 1,006 | 16,537 | | Forks | 119 | 1,341 | | Open issues | 98 | 579 | | Language | Java | Go | | Adopt for | ArcadeDB is a Multi-Model Database Management System that supports multiple data models (SQL, Cypher, Gremlin), and specializes in vector embeddings. Given its heritage as a conceptual fork of OrientDB and robust support | Weaviate is an open-source vector database with robust cloud-native architecture, supporting both automated and custom vector embedding. It integrates multiple machine learning models like OpenAI, Cohere, and HuggingFace | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Weaviate is distributed under BSD-3-Clause License, allowing free use in most contexts but requires preservation of copyright notices and disclaimers | | Categories | Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [arcadedb](/tools/arcadedata-arcadedb.md) | [weaviate](/tools/weaviate-weaviate.md) | | --- | --- | --- | | Open issues (now) | 98 | 579 | | Security scan | 1 medium (1 medium) | 12 low (12 low) | | Full report | [trust report](/tools/arcadedata-arcadedb/trust.md) | [trust report](/tools/weaviate-weaviate/trust.md) | **Typed relationship:** arcadedb _(alternative)_ weaviate Weaviate is an open-source vector database which provides scalable semantic search, similar to ArcadeDB's capabilities but focusing exclusively on vector and graph models. ## Decision facts: arcadedb - **Adopt for:** ArcadeDB is a Multi-Model Database Management System that supports multiple data models (SQL, Cypher, Gremlin), and specializes in vector embeddings. Given its heritage as a conceptual fork of OrientDB and robust support ## Decision facts: weaviate - **Pricing:** freemium - Open-source version is available for free; Weaviate Cloud offers premium paid plans with enterprise-level features. - **Requirements:** Min 2 GB RAM; Requires Docker; Requires a container environment like Docker or Kubernetes for deployment.; Supports importing pre-generated vector embeddings along with objects. - **Adopt for:** Weaviate is an open-source vector database with robust cloud-native architecture, supporting both automated and custom vector embedding. It integrates multiple machine learning models like OpenAI, Cohere, and HuggingFace - **License detail:** Weaviate is distributed under BSD-3-Clause License, allowing free use in most contexts but requires preservation of copyright notices and disclaimers ## Choose when ### Choose arcadedb if… - arcadedb is primarily Java; weaviate is Go. - License: arcadedb is Apache-2.0, weaviate is BSD-3-Clause. - Weaviate is an open-source vector database which provides scalable semantic search, similar to ArcadeDB's capabilities but focusing exclusively on vector and graph models. - Tags unique to arcadedb: distributed, docker, embedded, document. - You require seamless integration with various query languages such as SQL, Cypher, or Gremlin for querying different types of data. ### Choose weaviate if… - weaviate is primarily Go; arcadedb is Java. - License: weaviate is BSD-3-Clause, arcadedb is Apache-2.0. - Pricing: Open-source version is available for free; Weaviate Cloud offers premium paid plans with enterprise-level features.. - Requirements: Min 2 GB RAM; Requires Docker; Requires a container environment like Docker or Kubernetes for deployment.; Supports importing pre-generated vector embeddings along with objects.. - Weaviate is an open-source vector database which provides scalable semantic search, similar to ArcadeDB's capabilities but focusing exclusively on vector and graph models. - Tags unique to weaviate: grpc, information-retrieval, mlops, approximate-nearest-neighbor-search. - Also covers Data & Retrieval. - When you require a scalable solution for semantic search that can integrate both object data and vectors efficiently. ## When NOT to use arcadedb - You are building an application that requires real-time processing capabilities and microsecond latencies, as ArcadeDB’s focus on vector embedding support and multi-model querying might not optimizeit ## When NOT to use weaviate - In contexts where an open-source solution is not preferred or compliance requires proprietary software. - For projects that do not require the combination of vector similarity search with structured filtering and might benefit from a more specialized database solution. - When the desired deployment environment does not align with Docker, Kubernetes, or major cloud platforms supported by Weaviate. ## Common questions ### What is the difference between arcadedb and weaviate? arcadedb: Multi Model DBMS Built for Extreme Performance. weaviate: Open-source vector database for scalable semantic search. See the comparison table for live GitHub stats and shared categories. ### When should I choose arcadedb over weaviate? Choose arcadedb over weaviate when arcadedb is primarily Java; weaviate is Go; License: arcadedb is Apache-2.0, weaviate is BSD-3-Clause; Weaviate is an open-source vector database which provides scalable semantic search, similar to ArcadeDB's capabilities but focusing exclusively on vector and graph models; Tags unique to arcadedb: distributed, docker, embedded, document; You require seamless integration with various query languages such as SQL, Cypher, or Gremlin for querying different types of data. ### When should I choose weaviate over arcadedb? Choose weaviate over arcadedb when weaviate is primarily Go; arcadedb is Java; License: weaviate is BSD-3-Clause, arcadedb is Apache-2.0; Pricing: Open-source version is available for free; Weaviate Cloud offers premium paid plans with enterprise-level features.; Requirements: Min 2 GB RAM; Requires Docker; Requires a container environment like Docker or Kubernetes for deployment.; Supports importing pre-generated vector embeddings along with objects.; Weaviate is an open-source vector database which provides scalable semantic search, similar to ArcadeDB's capabilities but focusing exclusively on vector and graph models; Tags unique to weaviate: grpc, information-retrieval, mlops, approximate-nearest-neighbor-search; Also covers Data & Retrieval; When you require a scalable solution for semantic search that can integrate both object data and vectors efficiently. ### When should I avoid arcadedb? You are building an application that requires real-time processing capabilities and microsecond latencies, as ArcadeDB’s focus on vector embedding support and multi-model querying might not optimizeit ### When should I avoid weaviate? In contexts where an open-source solution is not preferred or compliance requires proprietary software. For projects that do not require the combination of vector similarity search with structured filtering and might benefit from a more specialized database solution. When the desired deployment environment does not align with Docker, Kubernetes, or major cloud platforms supported by Weaviate. ### Is arcadedb or weaviate more popular on GitHub? weaviate has more GitHub stars (16,537 vs 1,006). Stars measure visibility, not whether either tool fits your constraints. ### Are arcadedb and weaviate open source? Yes - both are open-source projects on GitHub (arcadedb: Apache-2.0, weaviate: BSD-3-Clause). ### Where can I find alternatives to arcadedb or weaviate? GraphCanon lists graph-backed alternatives at /tools/arcadedata-arcadedb/alternatives and /tools/weaviate-weaviate/alternatives (/tools/arcadedata-arcadedb/alternatives.md, /tools/weaviate-weaviate/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/arcadedata-arcadedb-vs-weaviate-weaviate.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, arcadedb or weaviate? arcadedb: Very active. weaviate: 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 arcadedb and weaviate? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: arcadedb: /tools/arcadedata-arcadedb/trust; weaviate: /tools/weaviate-weaviate/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arcadedata-arcadedb`](/api/graphcanon/graph?tool=arcadedata-arcadedb) - 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/_