Dragonfly, a multi-threaded Redis-compatible data store.
In short: Dragonfly is a modern in-memory data store, wire-compatible with Redis and Memcached, built on a multi-threaded shared-nothing architecture. It scales vertically across CPU cores. Whether it can consolidate a multi-node Redis workload depends on capacity, failure-domain, durability, and latency tests against the target environment.
We validate Redis and Memcached client compatibility, size the target from observed workload data, and define availability objectives, recovery behavior, and operational ownership in the engagement scope.
Dragonfly · multi-threaded
Shared-nothing · 1 node = a Redis cluster
0.00M
98.5%
0
90.0%
[OK] snapshot: point-in-time saved, 0 fork stalls
[INF] sched: shared-nothing, 32 threads balanced
[OK] compat: Redis + Memcached wire protocol
[INF] repl: replica streaming, offset caught up
Representative fleet view · illustrative metrics
Illustrative operating profile - example fleet and outcome figures, not audited customer results.
0+
Dragonfly Nodes Managed
0.99%
Uptime SLA
0M+
Peak Ops / sec (1 node)
0%
Avg Infra Cost Savings
Full-spectrum Dragonfly engineering
From a sharded Redis cluster to a single Dragonfly node - we plan it, migrate it, and run it.
Performance Engineering
Tune Dragonfly's multi-threaded, shared-nothing engine to saturate every core - one node where a Redis cluster used to live.
Vertical Scaling
Right-size a single Dragonfly instance to replace a multi-node Redis cluster - no resharding, no client-side hashing.
High Availability
Primary/replica replication, snapshotting, and failover design for a resilient in-memory tier.
Redis/Memcached Migration
Drop-in, wire-compatible cutover from Redis or Memcached - your existing clients and commands keep working.
Cloud & Kubernetes
Deploy Dragonfly on Kubernetes with the operator, persistent snapshots, and rolling upgrades.
24/7 Managed DBA
Round-the-clock monitoring, memory-efficiency tuning, snapshot verification, and incident response.
Every core, working for you
Redis leaves most of your CPU idle. Dragonfly's shared-nothing engine spreads work across all cores in one process - higher throughput, lower memory, fewer nodes to operate.
Throughput Performance
Illustrative target25×
Throughput per node
70%
Cost reduction
Illustrative workload optimization scenarios
9 shards
1 node
9-shard Redis cluster, ops overhead
The fix
Consolidated to single Dragonfly node, 25M ops/s
64GB
44GB
Redis RAM ceiling on same dataset
The fix
Dashtable layout, 30% less RAM per key
Reshard
Add vCPU
Cluster resharding downtime on growth
The fix
Scale cores vertically, no resharding step
0.00%
Node Uptime
<0s
Failover RTO
0ms
Replica Lag
Resilient by design
Primary/replica replication, point-in-time snapshots, and automated failover keep your in-memory tier online - without the operational weight of a multi-shard cluster.
A P1, handled against the contracted response target.
When memory pressure or a hot key threatens your cache tier, a named engineer responds with a runbook - not a ticket queue.
Redis cluster resharding stalled - hot shard saturated
Named Dragonfly engineer in under 15 min, not a queue
9 Redis shards under-utilizing cores, uneven keys
Migrated to a single Dragonfly node, no resharding
Hot shard gone, 4.2M ops/s on 1 node - total 12 min
Pre-Migration Assessment
Redis / Memcached → Dragonfly (wire-compatible)
Estimated cutover window: < 5 minutes
Move off Redis without rewriting code
Dragonfly speaks the Redis and Memcached protocols, so your clients keep working. Moving off Redis? We validate command coverage, run a dual-read window, and cut over with a rollback plan.
Specialized Dragonfly Services
Common questions about Dragonfly & Redis migration
What is Dragonfly?
Dragonfly is a modern in-memory data store that is wire-compatible with Redis and Memcached, built on a multi-threaded, shared-nothing architecture. It scales vertically across CPU cores, so a single node can replace a multi-node Redis cluster while using less memory.
Is Dragonfly a drop-in replacement for Redis?
For most workloads, yes. Dragonfly speaks the Redis (RESP) protocol, so existing clients and most commands work unchanged. We validate command coverage for your workload before cutover and run a dual-read verification window.
How does Dragonfly compare to a Redis Cluster?
Redis is single-threaded per process, so scaling means running many shards and managing client-side hashing/resharding. Dragonfly uses all cores in one process - you scale a single node vertically, eliminating cluster topology, resharding, and cross-slot limitations.
Do you offer 24/7 Dragonfly support?
Yes. Eligible support agreements provide round-the-clock monitoring, memory-efficiency tuning, snapshot verification, and incident response with severity-based targets stated in the signed contract.
Dragonfly information, checked against primary documentation
JusDB reviews technology-specific claims against the vendor or project's official documentation. Performance examples without a linked case study are labeled illustrative; actual results depend on workload, data model, version, topology, infrastructure, and test method.
Technically reviewed by the JusDB Database Reliability Engineering team on .
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