Dragonfly - The Fastest In-Memory Data Store
Mai 21, às 05:17
3 min de leitura
The most performant in-memory data store on Earth.
Dragonfly is a drop-in Redis® replacement that is high-performance, low-complexity, and built for scale. Dragonfly's modern architecture enables it to scale vertically to support millions of requests per second and terabyte-sized workloads, all on a single instance.
Benchmark on AWS r6gn.16xlarge. Snapshot benchmark on AWS c6gn.16xlarge. Source.
Fully compatible with Redis
Dragonfly is a drop-in Redis replacement, meaning it uses the same APIs and is compatible with all of the same SDKs and tooling. Teams that switch from Redis to Dragonfly get huge performance gains and simpler system to operate, all without changing code.
With non-contending, multi-threaded processes, Dragonfly is architected to deliver the performance that modern applications require: millions of operations per second, all from a single instance.View the benchmarks
Snapshotting speed (MB/ Sec)
QPS benchmark on AWS r6gn.16xlarge. Snapshot benchmark on AWS r6gd.16xlarge.Source
Faster snapshotting than Redis
Dragonfly is architected to scale vertically on a single machine, saving teams the cost and complexity of managing a multi-node cluster. For in-memory datasets up to 1TB, Dragonfly offers the simplest and most reliable scale on the market.
In-memory datasets on a single instance
Dragonfly utilizes unique and innovative algorithms and data structures, including dashtable and denseSet . This makes Dragonfly on average 30% more efficient than Redis, meaning you can achieve the same performance and scale on less hardware, significantly reducing total infrastructure costs. In addition, Dragonfly is much more simple to operate, resulting in a far lower total cost of ownership.
Memory usage under BGSAVE. Filling with 5GB of data using debug populate 5000000 key 1024, sending the update traffic with memtier, and snapshotting with bgsave. Source
A new in-memory data store, architected for today
While classic chaining hash-tables are built upon a dynamic array of linked-lists, Dragonfly's dashtable is a dynamic array of flat hash-tables of constant size. This design allows for much better memory efficiency.
High Hit Ratio
Dragonfly utilizes a unique 'least frequenty recently used' cache policy. When compared to Redis' LRU cache policy, LFRU is resistant to fluctuations in traffic, does not require random sampling, has zero memory overhead per item, and has a very small run-time overhead.
Dragonfly's new in-memory engine, optimized for throughput, uses a thread-per-core architecture without locks to deliver stable and low latencies. By implementing true async interfaces, Dragonfly takes full advantage of the underlying hardware to deliver maximum performance.
Start building today
Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.
Hoje, às 19:52
Hoje, às 19:26
AI | Techcrunch
Hoje, às 18:08
Hoje, às 18:08
Hoje, às 17:02
Hoje, às 16:58
Hoje, às 16:37
Hoje, às 16:10
AI | Techcrunch
Hoje, às 16:03
Hoje, às 16:02