Comparison
arcadedb vs weaviate
arcadedb (Multi Model DBMS Built for Extreme Performance) vs weaviate (Open-source vector database for scalable semantic search) - live GitHub stats and typed graph relationships, not marketing.
Markdown twin · arcadedb alternatives · weaviate alternatives
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Tagline
- arcadedb
- Multi Model DBMS Built for Extreme Performance
- weaviate
- Open-source vector database for scalable semantic search
Stars
- arcadedb
- 1.0k
- weaviate
- 17k
Forks
- arcadedb
- 119
- weaviate
- 1.3k
Open issues
- arcadedb
- 98
- weaviate
- 579
Language
- arcadedb
- Java
- weaviate
- Go
Adopt for
- arcadedb
- 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
- 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
- arcadedb
- -
- weaviate
- -
Runtime
- arcadedb
- -
- weaviate
- -
License
- arcadedb
- Apache-2.0
- weaviate
- Weaviate is distributed under BSD-3-Clause License, allowing free use in most contexts but requires preservation of copyright notices and disclaimers
Last pushed
- arcadedb
- Jul 8, 2026
- weaviate
- Jul 8, 2026
Categories
- arcadedb
- Vector Databases
- weaviate
- Data & Retrieval, Vector Databases
Trust and health
Open issues (now)
- arcadedb
- 98
- weaviate
- 579
Security scan
- arcadedb
- 1 medium (1 medium)
- weaviate
- 12 low (12 low)
Full report
- arcadedb
- Trust report
- weaviate
- Trust report
Typed relationship
arcadedb alternative weaviateWeaviate is an open-source vector database which provides scalable semantic search, similar to ArcadeDB's capabilities but focusing exclusively on vector and graph models.
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.
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
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 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.
Explore
arcadedb trust report →weaviate trust report →Vector Databases category →Data & Retrieval category →All comparisonsStack workflowsTrending tools
Related comparisons
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.