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Databases · head to head

Dragonfly vs Apache Pulsar

Dragonfly logo

Dragonfly

Databases

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

From
Free
Rated
-
Full reviewWebsite
Apache Pulsar logo

Apache Pulsar

Databases

Cloud-native messaging and streaming with separated storage

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; Apache Pulsar more components than Kafka: brokers, BookKeeper and ZooKeeper each need operating
  • They diverge on capability: Dragonfly covers Redis API compatibility, Apache Pulsar covers Separated storage.

Where they differ

Only the attributes on which Dragonfly and Apache Pulsar actually diverge.

Attributes where Dragonfly and Apache Pulsar differ
AttributeDragonflyApache Pulsar
Pricing modelUsage-based cloud pricing with flexible tiersOpen source, no licence fee
PlatformsCloud, AWS, GCP, AzureLinux, Docker, Kubernetes, Self-hosted

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 Apache Pulsar

  • Separated storage
  • Queuing and streaming
  • Built-in multi-tenancy
  • Geo-replication

What people use each for

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

Dragonfly

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

Apache Pulsar

  • Platforms needing both work queues and replayable streams without running two systemsnot Dragonfly
  • Multi-tenant messaging where isolation between teams is a requirementnot Dragonfly
  • Deployments where storage and traffic grow at genuinely different ratesnot 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

Apache Pulsar

  • More components than Kafka: brokers, BookKeeper and ZooKeeper each need operating
  • Correspondingly harder to run well, and the expertise is rarer than Kafka expertise
  • A much smaller ecosystem of connectors, tooling and hiring pool than Kafka
  • The architectural advantages only pay off at a scale most deployments never reach

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

Apache Pulsar

Free
  • Apache PulsarFree
    • Full functionality
    • No usage limits
    • Community support

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 Apache Pulsar if

  • You need separated storage.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want queuing and streaming.
Apache Pulsar review

Questions people ask

Is Dragonfly or Apache Pulsar better?
Neither clearly leads. Dragonfly starts at Free and Apache Pulsar at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dragonfly or Apache Pulsar?
Dragonfly starts at Free and Apache Pulsar at Free.
Does Dragonfly or Apache Pulsar run on more platforms?
Dragonfly runs on Cloud, AWS, GCP, Azure. Apache Pulsar runs on Linux, Docker, Kubernetes, Self-hosted.
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 Apache Pulsar is typically brought in for.
What can Dragonfly do that Apache Pulsar cannot?
Dragonfly covers Redis API compatibility, Thread-per-core architecture, High-performance caching, Memory efficiency. Apache Pulsar covers Separated storage, Queuing and streaming, Built-in multi-tenancy, Geo-replication.

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
Apache Pulsar: Is Apache Pulsar free?

Yes, open source under the Apache Software Foundation.

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
Apache Pulsar: Pulsar or Kafka?

Pulsar separates storage from compute and covers queuing and streaming in one system. Kafka has a far larger ecosystem and hiring pool. Most teams should have a specific reason before choosing Pulsar.

Apache Pulsar: Why does separated storage matter?

Brokers hold no data, so adding or replacing one requires no rebalancing, and storage can grow without adding serving capacity.

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