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ArangoDB

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Graph, vector, document and search in one engine, aimed at AI context

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  • Deployment Cloud Based, On Premise, SaaS
  • Starting price Not published
  • Free trial Available
  • Best for Small Business, Medium Business, Large Enterprise

What is ArangoDB?

ArangoDB is a contextual data platform unifying graph, vector, document and search in a single engine, positioned for building AI-powered applications without assembling several specialised databases.

The multi-model argument has become considerably stronger with retrieval-augmented AI, and the reason is specific. A modern AI application typically needs vector search for semantic retrieval, a graph for relationships between entities, documents for the source material and keyword search for exact matching, and assembling four systems means keeping four copies of the same data consistent. One engine holding all four removes both the synchronisation and the arguments about which copy is authoritative.

Positioning as the context layer for enterprise AI is a precise claim rather than a slogan. Grounding a model in an organisation's own knowledge is a retrieval problem across exactly those four access patterns, and the quality of the answer depends on being able to combine them in one query rather than in application code.

The honest counterweight is that a single engine doing four jobs will rarely beat a specialist at any one of them, and a team whose workload is overwhelmingly one access pattern should weigh that. The platform is offered as the Arango Contextual Data Platform and the Arango Platform Suite as an operations layer, with pricing and deployment options published on the site but no rate captured.

Key Features of ArangoDB

  • Multi-model single engine
  • Native graph traversal
  • Vector search for embeddings
  • Document storage
  • Full-text search
  • One query across access patterns
  • AI retrieval grounding
  • Contextual data platform
  • Arango Platform Suite operations layer
  • Self-managed and cloud deployment
  • Reduced data duplication
  • Enterprise scale operation

ArangoDB Pricing

Not published

Not published

No rate is published. Pricing is quoted per customer or billed on usage rather than as published plan tiers.

ArangoDB Specifications

Deployment
  • Cloud Based
  • On Premise
  • SaaS
Desktop
  • Web App
  • Linux
  • Windows
  • Mac
Built for
  • Small Business
  • Medium Business
  • Large Enterprise
Support
  • Email
  • Knowledge Base
Public API
Yes
Free trial
Yes
Free plan
No
Runs in browser
No
Customisable
No
Website
arangodb.com

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ArangoDB FAQs

Pricing and deployment options are published on the site but no rate was captured. Licences and managed instances are quoted according to deployment.

An AI application needs vector search for semantic retrieval, a graph for entity relationships, documents for source material and keyword search for exact matching. Four systems means four copies to keep consistent.

Grounding a model in an organisation's own knowledge is a retrieval problem across those four access patterns, and answer quality depends on combining them in one query rather than in application code.

A single engine doing four jobs will rarely beat a specialist at any one, so a team whose workload is overwhelmingly one access pattern should weigh that honestly.

As the Arango Contextual Data Platform with the Arango Platform Suite as a contextual operations layer, available across self-managed and cloud deployment options.