Softwr

Databases · head to head

Zilliz vs OpenSearch

Zilliz logo

Zilliz

Databases

Managed vector database and vector lakebase for AI applications

From
Free
Rated
-
Full reviewWebsite
OpenSearch logo

OpenSearch

Databases

Open-source search and analytics suite forked from Elasticsearch

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Zilliz pricing structure not publicly disclosed, requires sales contact; OpenSearch diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • They diverge on capability: Zilliz covers Vector indexing, OpenSearch covers Full-text search.

Where they differ

Only the attributes on which Zilliz and OpenSearch actually diverge.

Attributes where Zilliz and OpenSearch differ
AttributeZillizOpenSearch
Pricing modelcontact-salesOpen source, no licence fee; managed services billed separately
PlatformsCloud, Self-hostedLinux, Docker, Kubernetes, Self-hosted
Founded2017Unknown

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 Zilliz

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

Only in OpenSearch

  • Full-text search
  • OpenSearch Dashboards
  • Log analytics
  • Vector search

What people use each for

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

Zilliz

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

OpenSearch

  • Log and observability storage where an Apache-2.0 licence is a requirementnot Zilliz
  • Replacing Elasticsearch after the licence change without changing architecturenot Zilliz
  • Search plus analytics on one cluster rather than two systemsnot Zilliz

Where each one falls short

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

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

OpenSearch

  • Diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • Operationally heavy in the way Elasticsearch is: cluster sizing, shard strategy and JVM tuning are ongoing work
  • Smaller ecosystem of third-party tooling than Elasticsearch, which most integrations still target first
  • Overkill for plain application search, where a dedicated search engine is far simpler

Pricing, plan by plan

Zilliz

Free

No published plan breakdown. See the Zilliz review.

OpenSearch

Free
  • OpenSearchFree
    • Full functionality
    • Self-hosted
    • No usage limits

Which should you pick?

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

Choose OpenSearch if

  • You need full-text search.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want opensearch dashboards.
OpenSearch review

Questions people ask

Is Zilliz or OpenSearch better?
Neither clearly leads. Zilliz starts at Free and OpenSearch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Zilliz or OpenSearch?
Zilliz starts at Free and OpenSearch at Free.
Does Zilliz or OpenSearch run on more platforms?
Zilliz runs on Cloud, Self-hosted. OpenSearch runs on Linux, Docker, Kubernetes, Self-hosted.
Can I use Zilliz for free?
Both have a free tier, so you can try either at no cost before committing.
What is Zilliz best used for?
Zilliz is most often used for build retrieval-augmented generation (rag) systems, implement semantic search over documents, create multimodal search with text and images, power recommendation engines with vector similarity. Of those, build retrieval-augmented generation (rag) systems and implement semantic search over documents are not what OpenSearch is typically brought in for.
What can Zilliz do that OpenSearch cannot?
Zilliz covers Vector indexing, Distributed architecture, SQL interface, Tensor support. OpenSearch covers Full-text search, OpenSearch Dashboards, Log analytics, Vector search.

Answered from the vendors’ own pages

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
OpenSearch: Is OpenSearch free?

Yes, Apache 2.0 licensed under the Linux Foundation. Amazon OpenSearch Service is a paid managed option.

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
OpenSearch: Why does OpenSearch exist?

Elastic moved Elasticsearch off the Apache 2.0 licence in 2021. AWS forked the last Apache-licensed version, and the project now sits under the Linux Foundation.

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
OpenSearch: Is OpenSearch compatible with Elasticsearch?

It was at the 7.10 fork point. Both have developed independently since, so compatibility weakens with every release and should be verified for the features you use.

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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