Databases · head to head
Dragonfly vs OpenSearch

Dragonfly
Databases
High-performance Redis-compatible in-memory datastore with 25x better throughput
- From
- Free
- Rated
- -

OpenSearch
Databases
Open-source search and analytics suite forked from Elasticsearch
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Dragonfly flex tier starting at $36/month may be underpriced, requiring careful usage monitoring; OpenSearch diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
- They diverge on capability: Dragonfly covers Redis API compatibility, OpenSearch covers Full-text search.
- Prices and features above were last checked on 29 August 2026.
Where they differ
Only the attributes on which Dragonfly and OpenSearch actually diverge.
| Attribute | Dragonfly | OpenSearch |
|---|---|---|
| Pricing model | Usage-based cloud pricing with flexible tiers | Open source, no licence fee; managed services billed separately |
| Platforms | Cloud, AWS, GCP, Azure | Linux, 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 OpenSearch
- Full-text search
- OpenSearch Dashboards
- Log analytics
- Vector search
What people use each for
The jobs each tool is most often brought in to do.
Dragonfly
- High-throughput caching for web applicationsnot OpenSearch
- Real-time leaderboards and rankingsnot OpenSearch
- Message queue and event processingnot OpenSearch
- ML model feature serving at millisecond latenciesnot OpenSearch
- Gaming session state and player data storagenot OpenSearch
OpenSearch
- Log and observability storage where an Apache-2.0 licence is a requirementnot Dragonfly
- Replacing Elasticsearch after the licence change without changing architecturenot Dragonfly
- Search plus analytics on one cluster rather than two systemsnot 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
OpenSearch
- Diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
- Operationally heavy in the way Elasticsearch is: cluster sizing, shard strategy and JVM tuning are ongoing work
- Smaller ecosystem of third-party tooling than Elasticsearch, which most integrations still target first
- Overkill for plain application search, where a dedicated search engine is far simpler
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
OpenSearch
Free- OpenSearchFree
- Full functionality
- Self-hosted
- No usage limits
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.
Choose OpenSearch if
- You need full-text search.
- You want to start without paying.
- You work on Linux, Docker, Kubernetes, Self-hosted.
- You also want opensearch dashboards.
Questions people ask
- Is Dragonfly or OpenSearch better?
- Neither clearly leads. Dragonfly starts at Free and OpenSearch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dragonfly or OpenSearch?
- Dragonfly starts at Free and OpenSearch at Free.
- Does Dragonfly or OpenSearch run on more platforms?
- Dragonfly runs on Cloud, AWS, GCP, Azure. OpenSearch 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 OpenSearch is typically brought in for.
- What can Dragonfly do that OpenSearch cannot?
- Dragonfly covers Redis API compatibility, Thread-per-core architecture, High-performance caching, Memory efficiency. OpenSearch covers Full-text search, OpenSearch Dashboards, Log analytics, Vector search.
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.
SourceOpenSearch: Is OpenSearch free?
Yes, Apache 2.0 licensed under the Linux Foundation. Amazon OpenSearch Service is a paid managed option.
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.
SourceOpenSearch: Why does OpenSearch exist?
Elastic moved Elasticsearch off the Apache 2.0 licence in 2021. AWS forked the last Apache-licensed version, and the project now sits under the Linux Foundation.
OpenSearch: Is OpenSearch compatible with Elasticsearch?
It was at the 7.10 fork point. Both have developed independently since, so compatibility weakens with every release and should be verified for the features you use.
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