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Databases · head to head

StarRocks vs Zilliz

StarRocks logo

StarRocks

Databases

Apache 2.0 MPP analytical database built for joins on open table formats

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: StarRocks self-hosting is a genuine operations job: frontend and backend node roles, tablet distribution, compaction and materialised view refresh all need an owner, and there is no small-team-friendly single-binary mode.; Zilliz pricing structure not publicly disclosed, requires sales contact
  • They diverge on capability: StarRocks covers Cost-based optimiser, Zilliz covers Vector indexing.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which StarRocks and Zilliz actually diverge.

Attributes where StarRocks and Zilliz differ
AttributeStarRocksZilliz
Pricing modelOpen source, no licence feecontact-sales
PlatformsLinux, Docker, KubernetesCloud, Self-hosted
FoundedUnknown2017

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 StarRocks

  • Cost-based optimiser
  • Lakehouse query engine
  • Primary key tables
  • Materialised views
  • Shared-data mode
  • MySQL wire protocol

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.

StarRocks

  • Customer-facing analytics where queries join a fact table to several dimensions and must return in well under a secondnot Zilliz
  • Querying an Iceberg lakehouse directly without copying data into a proprietary warehouse formatnot Zilliz
  • Replacing a ClickHouse deployment that has become unmanageable because every new question needs another denormalised tablenot Zilliz
  • Real-time analytics fed by change data capture where rows must be updated in place rather than appendednot Zilliz

Zilliz

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

Where each one falls short

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

StarRocks

  • Self-hosting is a genuine operations job: frontend and backend node roles, tablet distribution, compaction and materialised view refresh all need an owner, and there is no small-team-friendly single-binary mode.
  • CelerData is by far the dominant contributor despite Linux Foundation stewardship, so the practical roadmap risk is the same as any single-vendor open source project.
  • It inherits a MySQL-flavoured SQL dialect from its Doris ancestry, so queries written for PostgreSQL, Snowflake or Trino need rewriting rather than porting.
  • Ecosystem support is thinner than ClickHouse or Trino: fewer client libraries, fewer managed hosting options and a much smaller pool of engineers who have run it in production.
  • Memory pressure under concurrent large joins is a common production failure, and the tuning knobs for query memory limits are unforgiving compared with a cloud warehouse that just scales.

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

StarRocks

Free
  • StarRocksFree
    • Apache 2.0 licence
    • Linux Foundation governance
    • No usage or node limits
  • CelerData Cloud$undefined/year
    • Managed StarRocks from the primary contributor
    • BYOC and serverless deployment options
    • Enterprise support and SLAs

Zilliz

Free

No published plan breakdown. See the Zilliz review.

Which should you pick?

Choose StarRocks if

  • You need cost-based optimiser.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want lakehouse query engine.
StarRocks 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 StarRocks or Zilliz better?
Neither clearly leads. StarRocks 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, StarRocks or Zilliz?
StarRocks starts at Free and Zilliz at Free.
Does StarRocks or Zilliz run on more platforms?
StarRocks runs on Linux, Docker, Kubernetes. Zilliz runs on Cloud, Self-hosted.
Can I use StarRocks for free?
Both have a free tier, so you can try either at no cost before committing.
What is StarRocks best used for?
StarRocks is most often used for customer-facing analytics where queries join a fact table to several dimensions and must return in well under a second, querying an iceberg lakehouse directly without copying data into a proprietary warehouse format, replacing a clickhouse deployment that has become unmanageable because every new question needs another denormalised table, real-time analytics fed by change data capture where rows must be updated in place rather than appended. Of those, customer-facing analytics where queries join a fact table to several dimensions and must return in well under a second and querying an iceberg lakehouse directly without copying data into a proprietary warehouse format are not what Zilliz is typically brought in for.
What can StarRocks do that Zilliz cannot?
StarRocks covers Cost-based optimiser, Lakehouse query engine, Primary key tables, Materialised views. Zilliz covers Vector indexing, Distributed architecture, SQL interface, Tensor support.

Answered from the vendors’ own pages

StarRocks: Is StarRocks open source?

Yes, Apache 2.0, governed under the Linux Foundation since 2023.

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
StarRocks: How does it differ from ClickHouse?

StarRocks is built for joins across a star schema with a cost-based optimiser; ClickHouse is fastest on denormalised single tables.

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
StarRocks: Who maintains it?

CelerData, formerly StarRocks Inc, is the dominant contributor and sells the managed service.

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
StarRocks: Can it query Iceberg tables directly?

Yes, along with Hudi, Delta Lake, Hive and Paimon, with a local cache for repeat queries.

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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