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Databases · head to head

StarRocks vs Vespa

StarRocks logo

StarRocks

Databases

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

From
Free
Rated
-
Full reviewWebsite
Vespa logo

Vespa

Databases

Distributed AI search platform for retrieval, ranking, and inference

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.; Vespa pricing not publicly listed, requires contacting sales
  • They diverge on capability: StarRocks covers Cost-based optimiser, Vespa covers Vector search.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which StarRocks and Vespa actually diverge.

Attributes where StarRocks and Vespa differ
AttributeStarRocksVespa
Pricing modelOpen source, no licence feecontact-sales
PlatformsLinux, Docker, KubernetesCloud, Self-hosted
FoundedUnknown2023

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 Vespa

  • Vector search
  • Text and structured search
  • Machine-learned ranking
  • Real-time serving
  • SQL interface
  • Automatic scaling
  • Open-source

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 Vespa
  • Querying an Iceberg lakehouse directly without copying data into a proprietary warehouse formatnot Vespa
  • Replacing a ClickHouse deployment that has become unmanageable because every new question needs another denormalised tablenot Vespa
  • Real-time analytics fed by change data capture where rows must be updated in place rather than appendednot Vespa

Vespa

  • Build RAG systems with semantic search over documentsnot StarRocks
  • Power e-commerce search with ML rankingnot StarRocks
  • Create recommendation engines for personalizationnot StarRocks
  • Implement real-time search for news or feedsnot StarRocks
  • Deploy private semantic search over sensitive datanot 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.

Vespa

  • Pricing not publicly listed, requires contacting sales
  • Steeper learning curve compared to simpler search tools
  • Operational complexity for self-hosted deployments
  • Smaller ecosystem compared to cloud-native 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

Vespa

Free

No published plan breakdown. See the Vespa 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 Vespa if

  • You need vector search.
  • You want to start without paying.
  • You work on Cloud, Self-hosted.
  • You also want text and structured search.
Vespa review

Questions people ask

Is StarRocks or Vespa better?
Neither clearly leads. StarRocks starts at Free and Vespa at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, StarRocks or Vespa?
StarRocks starts at Free and Vespa at Free.
Does StarRocks or Vespa run on more platforms?
StarRocks runs on Linux, Docker, Kubernetes. Vespa 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 Vespa is typically brought in for.
What can StarRocks do that Vespa cannot?
StarRocks covers Cost-based optimiser, Lakehouse query engine, Primary key tables, Materialised views. Vespa covers Vector search, Text and structured search, Machine-learned ranking, Real-time serving.

Answered from the vendors’ own pages

StarRocks: Is StarRocks open source?

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

Vespa: Is Vespa open-source?

Yes, Vespa is open-source under the Apache 2.0 license. The code is available on GitHub, and you can self-host or use the managed cloud service.

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.

Vespa: What latency can Vespa achieve?

Vespa is designed for sub-100 millisecond latencies with thousands of queries per second, suitable for real-time search and recommendation applications.

Source
StarRocks: Who maintains it?

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

Vespa: Does Vespa support vector search?

Yes, Vespa provides native vector search capabilities alongside text, structured data, and tensor operations for building comprehensive search and AI applications.

Source
StarRocks: Can it query Iceberg tables directly?

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

Vespa: What is the pricing model for Vespa Cloud?

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

Source
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