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Databases · head to head

Dragonfly vs StarRocks

Dragonfly logo

Dragonfly

Databases

High-performance Redis-compatible in-memory datastore with 25x better throughput

From
Free
Rated
-
Full reviewWebsite
StarRocks logo

StarRocks

Databases

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dragonfly flex tier starting at $36/month may be underpriced, requiring careful usage monitoring; 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.
  • They diverge on capability: Dragonfly covers Redis API compatibility, StarRocks covers Cost-based optimiser.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dragonfly and StarRocks actually diverge.

Attributes where Dragonfly and StarRocks differ
AttributeDragonflyStarRocks
Pricing modelUsage-based cloud pricing with flexible tiersOpen source, no licence fee
PlatformsCloud, AWS, GCP, AzureLinux, Docker, Kubernetes

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 Dragonfly

  • Redis API compatibility
  • Thread-per-core architecture
  • High-performance caching
  • Memory efficiency
  • Real-time leaderboards
  • Message queue support
  • ML feature serving
  • Cloud deployment

Only in StarRocks

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

What people use each for

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

Dragonfly

  • High-throughput caching for web applicationsnot StarRocks
  • Real-time leaderboards and rankingsnot StarRocks
  • Message queue and event processingnot StarRocks
  • ML model feature serving at millisecond latenciesnot StarRocks
  • Gaming session state and player data storagenot StarRocks

StarRocks

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

Where each one falls short

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

Dragonfly

  • Flex tier starting at $36/month may be underpriced, requiring careful usage monitoring
  • Business tier $2,000/month represents significant jump in cost
  • Limited to in-memory storage, not suitable for cold data or archival
  • Bring-your-own-cloud requirement on Business tier adds operational complexity
  • Cloud availability dependent on AWS/GCP/Azure uptime

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.

Pricing, plan by plan

Dragonfly

Free
  • Free TierFree
    • 100 cloud credits for new signups
    • Equivalent to free trial
  • Business$2000/month
    • Starting price for enterprise offering
    • Bring-your-own-cloud deployment
    • Auto-scaling with custom SLAs
  • Enterprise$undefined/custom
    • Custom pricing
    • Any-cloud deployment
    • Custom instances and sizing

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

Which should you pick?

Choose Dragonfly if

  • You need redis api compatibility.
  • You want to start without paying.
  • You work on Cloud, AWS, GCP, Azure.
  • You also want thread-per-core architecture.
Dragonfly review

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

Questions people ask

Is Dragonfly or StarRocks better?
Neither clearly leads. Dragonfly starts at Free and StarRocks at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dragonfly or StarRocks?
Dragonfly starts at Free and StarRocks at Free.
Does Dragonfly or StarRocks run on more platforms?
Dragonfly runs on Cloud, AWS, GCP, Azure. StarRocks runs on Linux, Docker, Kubernetes.
Can I use Dragonfly for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dragonfly best used for?
Dragonfly is most often used for high-throughput caching for web applications, real-time leaderboards and rankings, message queue and event processing, ml model feature serving at millisecond latencies. Of those, high-throughput caching for web applications and real-time leaderboards and rankings are not what StarRocks is typically brought in for.
What can Dragonfly do that StarRocks cannot?
Dragonfly covers Redis API compatibility, Thread-per-core architecture, High-performance caching, Memory efficiency. StarRocks covers Cost-based optimiser, Lakehouse query engine, Primary key tables, Materialised views.

Answered from the vendors’ own pages

Dragonfly: How much faster is Dragonfly than Redis?

Dragonfly achieves 3.97M queries per second compared to Redis's 718K QPS, representing a 25x improvement. Memory efficiency is also 30% better.

Source
StarRocks: Is StarRocks open source?

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

Dragonfly: Can I migrate from Redis to Dragonfly without code changes?

Yes. Dragonfly maintains full API compatibility with Redis and Memcached, allowing drop-in replacement with minimal to no code modifications.

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.

StarRocks: Who maintains it?

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

StarRocks: Can it query Iceberg tables directly?

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

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