Introducing Dragonfly Cloud! Learn More

Dragonfly Cloud

Dragonfly Cloud on AWS 

Deploy the fastest, most efficient in-memory data store on the market to the AWS region of your choice.

Request a Dragonfly Cloud demo

80% lower costs than ElastiCache
10x performance
Scale effortlessly

Effortless Scale 

Dragonfly Cloud makes scaling simple. Rather than managing instances and clusters, with Dragonfly Cloud, you only need to manage memory capacity. Dragonfly Cloud will scale to handle even the most spiky and unpredictable traffic patterns. This allows you to consistently deliver a lightning-fast user experience, even when you are having your highest traffic day on record.

Lower Infrastructure Costs 

Dragonfly’s shared-nothing, multi-threaded architecture allows it to more efficiently utilize modern cloud hardware, resulting in the ability to run the same workloads on far less hardware. Redis Enterprise and ElastiCache customers can typically reduce their infrastructure costs by 30% and total costs by over 50% by migrating to Dragonfly Cloud.

Use Case:
ML Feature Store

Data Set:Peak QPS:
150GB450,000
Cost:
Dragonfly
$ 1,500
Redis Enterprise
$ 7,687
ElastiCache
$ 6,394
A financial institution was building a ML feature store to serve as a fraud detection model for their various web services. The service would need to scale to handle a lot of data as well as very spiky traffic, with peaks over 400,000 queries per second. They chose Dragonfly Cloud due to its ease of scaling and dramatically lower cost.

Drop-in Redis Replacement 

Dragonfly is fully compatible with both the Redis and Memcached APIs, meaning there are no code changes required to migrate. You can continue to use the same libraries, clients, and CLIs that you use today.

Cloud of Your Choice 

Dragonfly Cloud is available on the cloud and region of your choice, allowing for a secure and low-latency integration with the rest of your stack.

cloud choice diagram

Start building today 

Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.