Audience
Developers, cloud architects, and enterprises looking for a high-performance, cost-effective in-memory data store solution to handle large-scale, low-latency data workloads in cloud environments
About Dragonfly
Dragonfly is a drop-in Redis replacement that cuts costs and boosts performance. Designed to fully utilize the power of modern cloud hardware and deliver on the data demands of modern applications, Dragonfly frees developers from the limits of traditional in-memory data stores. The power of modern cloud hardware can never be realized with legacy software. Dragonfly is optimized for modern cloud computing, delivering 25x more throughput and 12x lower snapshotting latency when compared to legacy in-memory data stores like Redis, making it easy to deliver the real-time experience your customers expect. Scaling Redis workloads is expensive due to their inefficient, single-threaded model. Dragonfly is far more compute and memory efficient, resulting in up to 80% lower infrastructure costs. Dragonfly scales vertically first, only requiring clustering at an extremely high scale. This results in a far simpler operational model and a more reliable system.
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Product Details
Dragonfly Frequently Asked Questions
Dragonfly Product Features
Caching
Dragonfly is a high-performance cache and drop-in replacement for Redis, Valkey, and Memcached. It speaks the same protocols, so existing cache clients and application code work unchanged. Its multi-threaded architecture serves reads and writes across all CPU cores, handling up to 6 million operations per second on a single node with predictable low latency at peak traffic. Teams can consolidate large, sharded cache clusters onto fewer instances: Instacart reduced its cluster size by 70% while cutting average latency by 50%. A memory-efficient design stores more cached data per gigabyte, and a built-in cache mode with adaptive eviction keeps hit rates high without manual tuning. Use Dragonfly for application caching, session storage, rate limiting, leaderboards, and API response caching, self-hosted or fully managed on Dragonfly Cloud.
Database as a Service (DBaaS)
Dragonfly Cloud is a fully managed in-memory data store service built on Dragonfly, the Redis and Valkey compatible database designed for modern hardware. It handles provisioning, scaling, high availability, backups, and upgrades so engineering teams can focus on their applications instead of operating clusters. Because Dragonfly is multi-threaded and fully utilizes each instance, Dragonfly Cloud delivers more throughput per dollar than managed services built on single-threaded engines. Instacart reduced cluster size by 70% and average latency by 50%, and redBus doubled throughput while cutting latency in half. Existing Redis and Valkey clients and commands work unchanged, making migration from services like ElastiCache or Memorystore straightforward. Dragonfly Cloud supports caching, session storage, queues, real-time analytics, and AI workloads like feature stores and vector search.
In-Memory Databases
Dragonfly is a modern in-memory database engineered from the ground up for multi-core cloud hardware. Traditional in-memory stores like Redis run on a single thread, forcing expensive clustering as workloads grow. Dragonfly's multi-threaded, shared-nothing architecture uses every core, delivering up to 25x the throughput of Redis on the same hardware and up to 6 million operations per second per node. It is fully compatible with the Redis and Valkey APIs, so teams migrate without rewriting code. The Dashtable data structure cuts memory overhead by up to 40%, and fork-free snapshotting avoids the memory spikes that destabilize large instances. Companies including Instacart, redBus, and Meesho use Dragonfly to lower latency and reduce infrastructure costs. Available self-managed or as a fully managed service on Dragonfly Cloud.
Infrastructure-as-a-Service (IaaS)
Dragonfly is a high-performance in-memory data store built to get the most out of modern cloud infrastructure. Its multi-threaded, shared-nothing architecture uses every core on an instance, reaching up to 6 million operations per second on a single node, so teams run fewer, smaller machines instead of sprawling clusters. Dragonfly is compatible with the Redis and Valkey APIs, so existing applications migrate without code changes. For infrastructure and platform teams, that means lower compute and memory spend: Instacart cut its cluster size by 70%, and Meesho reported 60% cost savings. Dragonfly scales vertically first and adds horizontal scale only when needed, keeping topology simple and operations lean. Deploy it self-managed on any cloud VM or Kubernetes, or use Dragonfly Cloud to offload provisioning, scaling, and maintenance.
Key-Value Databases
Dragonfly is a high-throughput key-value database compatible with the Redis and Valkey APIs. It supports strings, hashes, lists, sets, sorted sets, streams, JSON, and more, so applications built on Redis clients run on Dragonfly without code changes. Its multi-threaded, shared-nothing design processes requests across all CPU cores in parallel, sustaining up to 6 million operations per second per node with consistent low latency under load. The Dashtable data structure reduces memory overhead by up to 40%, letting teams store more keys on less hardware. Snapshotting runs without the memory spikes of fork-based persistence, so large datasets stay stable during backups. Dragonfly handles very large datasets on a single node before clustering is needed, which simplifies operations. Run it self-hosted or fully managed on Dragonfly Cloud.