Databases · head to head
Apache Flink vs Dragonfly

Dragonfly
Databases
High-performance Redis-compatible in-memory datastore with 25x better throughput
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Apache Flink genuinely difficult: event time, watermarks and state backends are a real conceptual load before anything works; Dragonfly flex tier starting at $36/month may be underpriced, requiring careful usage monitoring
- They diverge on capability: Apache Flink covers Event-time processing, Dragonfly covers Redis API compatibility.
- Prices and features above were last checked on 29 August 2026.
Where they differ
Only the attributes on which Apache Flink and Dragonfly actually diverge.
| Attribute | Apache Flink | Dragonfly |
|---|---|---|
| Pricing model | Open source, no licence fee; managed services billed separately | Usage-based cloud pricing with flexible tiers |
| Platforms | Linux, Kubernetes, Docker, Self-hosted | Cloud, AWS, GCP, Azure |
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 Apache Flink
- Event-time processing
- Exactly-once state
- Batch and stream
- SQL interface
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
What people use each for
The jobs each tool is most often brought in to do.
Apache Flink
- Real-time aggregations and dashboards computed over an event streamnot Dragonfly
- Fraud and anomaly detection where patterns span a time windownot Dragonfly
- Joining two live streams where events arrive out of ordernot Dragonfly
Dragonfly
- High-throughput caching for web applicationsnot Apache Flink
- Real-time leaderboards and rankingsnot Apache Flink
- Message queue and event processingnot Apache Flink
- ML model feature serving at millisecond latenciesnot Apache Flink
- Gaming session state and player data storagenot Apache Flink
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Apache Flink
- Genuinely difficult: event time, watermarks and state backends are a real conceptual load before anything works
- Operationally heavy — job managers, task managers, checkpoint storage and state size are all yours to run and tune
- State grows with the workload, and large state changes recovery time and cost significantly
- Overkill where a scheduled batch job would answer the same question
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
Pricing, plan by plan
Apache Flink
Free- Apache FlinkFree
- Full functionality
- Self-hosted
- No usage limits
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
Which should you pick?
Choose Apache Flink if
- You need event-time processing.
- You want to start without paying.
- You work on Linux, Kubernetes, Docker, Self-hosted.
- You also want exactly-once state.
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.
Questions people ask
- Is Apache Flink or Dragonfly better?
- Neither clearly leads. Apache Flink starts at Free and Dragonfly at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Apache Flink or Dragonfly?
- Apache Flink starts at Free and Dragonfly at Free.
- Does Apache Flink or Dragonfly run on more platforms?
- Apache Flink runs on Linux, Kubernetes, Docker, Self-hosted. Dragonfly runs on Cloud, AWS, GCP, Azure.
- Can I use Apache Flink for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Apache Flink best used for?
- Apache Flink is most often used for real-time aggregations and dashboards computed over an event stream, fraud and anomaly detection where patterns span a time window, joining two live streams where events arrive out of order. Of those, real-time aggregations and dashboards computed over an event stream and fraud and anomaly detection where patterns span a time window are not what Dragonfly is typically brought in for.
- What can Apache Flink do that Dragonfly cannot?
- Apache Flink covers Event-time processing, Exactly-once state, Batch and stream, SQL interface. Dragonfly covers Redis API compatibility, Thread-per-core architecture, High-performance caching, Memory efficiency.
Answered from the vendors’ own pages
Apache Flink: Is Apache Flink free?
Yes, open source under the Apache Software Foundation. Managed services such as Amazon Managed Service for Apache Flink are billed separately.
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.
SourceApache Flink: Flink or Kafka?
They are complementary rather than alternatives. Kafka moves and stores events; Flink computes over them with windowing, joins and durable state.
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.
SourceApache Flink: What is event-time processing?
Computing based on when an event actually occurred rather than when it arrived. It is what makes results correct when data is late or out of order, and it is the main reason Flink is harder than it looks.
Related pages
More on Apache Flink
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- Dragonfly vs QuestDB
- Dragonfly vs Redpanda
- Dragonfly vs NATS
- Dragonfly vs OpenSearch
- Dragonfly vs Estuary
- Dragonfly vs RabbitMQ
- Dragonfly vs Materialize
- Dragonfly vs Oracle Database
- Dragonfly vs TimescaleDB
- Dragonfly vs Turso
- Dragonfly vs Amazon RDS
- Dragonfly vs DataGrip
- Dragonfly vs Amazon Redshift
- Dragonfly vs Valkey
- Dragonfly vs Memcached
- Dragonfly vs Readyset
- Dragonfly vs Apache Druid
- Dragonfly vs TiDB
- Dragonfly vs ScyllaDB
- Dragonfly vs Firebolt
- Dragonfly vs Amazon Aurora
- Dragonfly vs Couchbase
- Dragonfly vs turbopuffer
- Dragonfly vs Instaclustr
- Dragonfly vs Knack
- Dragonfly vs LanceDB
- Dragonfly vs Marqo
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