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Databases · head to head

Zilliz vs Readyset

Zilliz logo

Zilliz

Databases

Managed vector database and vector lakebase for AI applications

From
Free
Rated
-
Readyset logo

Readyset

Databases

Database caching and optimization that reduces infrastructure costs 30-70%

From
Free
Rated
-

The short version

  • Each has a real cost: Zilliz pricing structure not publicly disclosed, requires sales contact; Readyset pricing requires contacting sales team, making cost planning difficult
  • They diverge on capability: Zilliz covers Vector indexing, Readyset covers Automatic Query Optimization.

Where they differ

Only the attributes on which Zilliz and Readyset actually diverge.

Attributes where Zilliz and Readyset differ
AttributeZillizReadyset
Pricing modelcontact-salesMonthly or annual subscription based on cache size
Founded2017Unknown

Identical on both: starting price (Free), free tier (Yes), platforms (Cloud, Self-hosted), 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 Readyset

  • Automatic Query Optimization
  • SQL-Level Caching
  • Live Incremental Updates
  • Zero-Touch Integration
  • Query Interception
  • AI Query Protection

What people use each for

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

Zilliz

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

Readyset

  • Reducing database costs for AI workloads with unpredictable query patternsnot Zilliz
  • Improving read performance for frequently accessed data without hardware upgradesnot Zilliz
  • Protecting databases from performance degradation caused by agentic queriesnot Zilliz
  • Scaling read-heavy applications without database scaling costsnot 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

Readyset

  • Pricing requires contacting sales team, making cost planning difficult
  • Specific pricing tiers not disclosed publicly
  • Requires cache size estimation for cost calculation
  • Limited to read query caching, does not address write performance

Pricing, plan by plan

Zilliz

Free

No published plan breakdown. See the Zilliz review.

Readyset

Free
  • CommunityFree
    • Free tier for evaluation
    • 7-day trial available
  • Readyset CloudFree
    • Fully-managed AWS deployment
    • High availability
    • VPC peering support
  • Readyset PrivateFree
    • Self-hosted on your servers
    • Complete control
    • Custom deployment

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.

Choose Readyset if

  • You need automatic query optimization.
  • You want to start without paying.
  • You work on Cloud, Self-Hosted.
  • You also want sql-level caching.

Questions people ask

Is Zilliz or Readyset better?
Neither clearly leads. Zilliz starts at Free and Readyset at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Zilliz or Readyset?
Zilliz starts at Free and Readyset at Free.
Does Zilliz or Readyset run on more platforms?
Zilliz runs on Cloud, Self-hosted. Readyset runs on Cloud, 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 Readyset is typically brought in for.
What can Zilliz do that Readyset cannot?
Zilliz covers Vector indexing, Distributed architecture, SQL interface, Tensor support. Readyset covers Automatic Query Optimization, SQL-Level Caching, Live Incremental Updates, Zero-Touch Integration.

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
Readyset: Do I need to change my application code?

No, Readyset integrates transparently through query interception with zero code changes or schema modifications required.

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
Readyset: Is there a free trial?

Yes, Readyset offers a free 7-day trial that lets you test different cache sizes before committing to a paid plan.

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
Readyset: How does Readyset pricing work?

Readyset is available as a monthly or annual subscription charged based on the size of cache you need. Contact [email protected] for specific pricing.

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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