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Databases · head to head

ArangoDB vs Zilliz

ArangoDB logo

ArangoDB

Databases

Multi-model database for graph, document, and search

From
Free
Rated
-
Full reviewWebsite
Zilliz logo

Zilliz

Databases

Managed vector database and vector lakebase for AI applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: ArangoDB the company has repositioned around a wider platform, so ArangoDB is now described as the foundation inside Arango rather than the product itself; Zilliz pricing structure not publicly disclosed, requires sales contact
  • They diverge on capability: ArangoDB covers Multi-model Support, Zilliz covers Vector indexing.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which ArangoDB and Zilliz actually diverge.

Attributes where ArangoDB and Zilliz differ
AttributeArangoDBZilliz
Pricing modelfreemiumcontact-sales
PlatformsLinux, Windows, Mac, Docker, WebCloud, Self-hosted
Founded20142017

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in ArangoDB

  • Multi-model Support
  • AQL Query Language
  • Graph Traversals
  • Full-text Search
  • ACID Transactions
  • SmartGraphs
  • Satellite Collections
  • Foxx Microservices

Only in Zilliz

  • Vector indexing
  • Distributed architecture
  • SQL interface
  • Tensor support
  • Real-time search
  • Cloud-native
  • Open-source compatible

What people use each for

The jobs each tool is most often brought in to do.

ArangoDB

  • Graph, document and key-value data in one databasenot Zilliz
  • Vector and full-text search alongside graph traversalnot Zilliz
  • Avoiding separate stores for related and unstructured datanot Zilliz
  • Backing AI applications needing both graph context and vectorsnot Zilliz

Zilliz

  • Build retrieval-augmented generation (RAG) systemsnot ArangoDB
  • Implement semantic search over documentsnot ArangoDB
  • Create multimodal search with text and imagesnot ArangoDB
  • Power recommendation engines with vector similaritynot ArangoDB
  • Enable similarity search on user embeddingsnot ArangoDB

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

ArangoDB

  • The company has repositioned around a wider platform, so ArangoDB is now described as the foundation inside Arango rather than the product itself
  • Neither the community licence terms nor cloud pricing are stated on the main site
  • arangodb.com redirects to arango.ai

Zilliz

  • Pricing structure not publicly disclosed, requires sales contact
  • Operational complexity for self-hosted Milvus deployments
  • Learning curve for those unfamiliar with vector databases
  • Limited built-in analytics compared to some alternatives

Pricing, plan by plan

ArangoDB

Free
  • CommunityFree
    • All data models
    • AQL queries
    • Full-text search
  • ArangoGraph$99/month
    • Managed service
    • Graph analytics
    • Enterprise support

Zilliz

Free

No published plan breakdown. See the Zilliz review.

Which should you pick?

Choose ArangoDB if

  • You need multi-model support.
  • You want to start without paying.
  • You work on Linux, Windows, Mac, Docker, Web.
  • You also want aql query language.
ArangoDB review

Choose Zilliz if

  • You need vector indexing.
  • You want to start without paying.
  • You work on Cloud, Self-hosted.
  • You also want distributed architecture.
Zilliz review

Questions people ask

Is ArangoDB or Zilliz better?
Neither clearly leads. ArangoDB starts at Free and Zilliz at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ArangoDB or Zilliz?
ArangoDB starts at Free and Zilliz at Free.
Does ArangoDB or Zilliz run on more platforms?
ArangoDB runs on Linux, Windows, Mac, Docker, Web. Zilliz runs on Cloud, Self-hosted.
Can I use ArangoDB for free?
Both have a free tier, so you can try either at no cost before committing.
What is ArangoDB best used for?
ArangoDB is most often used for graph, document and key-value data in one database, vector and full-text search alongside graph traversal, avoiding separate stores for related and unstructured data, backing ai applications needing both graph context and vectors. Of those, graph, document and key-value data in one database and vector and full-text search alongside graph traversal are not what Zilliz is typically brought in for.
What can ArangoDB do that Zilliz cannot?
ArangoDB covers Multi-model Support, AQL Query Language, Graph Traversals, Full-text Search. Zilliz covers Vector indexing, Distributed architecture, SQL interface, Tensor support.

Answered from the vendors’ own pages

ArangoDB: How is ArangoDB priced?

ArangoDB offers Community Edition (free) and Enterprise Edition. Pricing is customized based on deployment model (self-managed, managed cloud AWS/GCP, or OEM/embedded) and customer requirements. Contact Arango for a quote.

Source
Zilliz: What is the difference between Milvus and Zilliz Cloud?

Milvus is the open-source vector database that you can self-host. Zilliz Cloud is the fully managed service built on Milvus that removes operational overhead and handles scaling automatically.

Source
ArangoDB: What deployment options does ArangoDB offer?

ArangoDB can be deployed self-managed on customer infrastructure, as managed cloud (Arango Managed Platform on AWS/GCP), or as OEM/embedded solutions.

Source
Zilliz: How many vectors can Zilliz handle?

Milvus and Zilliz Cloud can store and search billions of vectors through their distributed architecture that separates storage and compute layers.

Source
Zilliz: Is Milvus open-source?

Yes, Milvus is open-source under the Apache License 2.0 and is part of the LF AI & Data Foundation.

Source
Zilliz: What pricing does Zilliz Cloud offer?

Zilliz Cloud pricing is not publicly listed and requires contacting their team to discuss your specific scale and use case requirements.

Source
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