Dragonfly (@dragonflydbio) / X

Dragonfly

1,100 posts

Dragonfly

@dragonflydbio

Dragonfly is a drop-in Redis replacement, delivering 25X better performance at 80% lower cost. Host it yourself for free or pay per GB for Dragonfly Cloud.

Joined June 2022

Dragonfly
@dragonflydbio
12h
Dragonfly 1.39 is here with major new search capabilities, performance improvements (as always), and a lot more. Search: `FT.HYBRID` brings native text + vector fusion (LINEAR and RRF strategies) to a Redis-compatible interface, introducing a single command for RAG pipelines,
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Dragonfly
@dragonflydbio
Jun 9
We're in LA! 🌴 AWS Summit is tomorrow — find us at booth 244 to talk in-memory infrastructure built for extreme throughput at scale. Come say hi! @awscloud #AWSSummits
82
Dragonfly
@dragonflydbio
Jun 3
Dragonfly Ascent is our first-ever community conference — a virtual event featuring talks from the Dragonfly community. 🎙️ Call for Speakers is now open. Have a story to tell? We want to hear from you. ✨ Submit a talk → hubs.la/Q04k0jsq0
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Dragonfly
@dragonflydbio
Jun 1
Dragonfly SSD Data Tiering is GA. Hot data in RAM. Warm and cold data on NVMe. Keys always in memory. Zero application changes. Dragonfly is the only source-available, Redis-compatible in-memory data store with SSD tiering. Redis and Valkey don't have it. In production at
dragonflydb.io
SSD Data Tiering Is Generally Available
Dragonfly SSD Data Tiering is now GA. Scale beyond RAM limits on a single node — no resharding, no code changes. The only source-available Redis-compatible store with SSD tiering.
160
Dragonfly
@dragonflydbio
May 27
Dragonfly has been named to the 2026 @Redpoint InfraRed 100, the 100 private companies defining the next era of cloud infrastructure. Multi-threaded. Shared-nothing. 25x the throughput of Redis on the same instance. Thank you to our customers, our community, and Redpoint.
177
Dragonfly
@dragonflydbio
May 7
Teams are replacing up to 10 Redis instances with a single Dragonfly instance using ACL database selectors. Logical isolation + security enforcement. No key prefix conventions. No discipline required from devs. How it works → hubs.la/Q04fNLD60
372
Dragonfly
@dragonflydbio
Apr 29
A cluster that looks healthy on average can still have one shard quietly running out of memory. You won't see the problem until a hot shard hits its limit and by then you're either dealing with evictions or scrambling to resize. We shipped shard memory balancing in Dragonfly
Memory-Aware Rebalancing Is Now Automatic in Dragonfly Cloud
From dragonflydb.io
487
Dragonfly
@dragonflydbio
Apr 16
Running Redis or Valkey with heavy TTL usage? The expire table is a real cost — a parallel structure you maintain just to track which keys should die. In Dragonfly v1.38, we removed it. Expiry metadata is now embedded directly in each key. On a 10M small-value workload, memory
273
Dragonfly
@dragonflydbio
Mar 24
Redis was built in a single-threaded era. Modern cloud servers have 64, 96+ cores. Redis uses one of them. At multi-terabyte scale, that mismatch compounds fast: more shards, more nodes, more ops overhead, higher cost. We wrote about what a rethink actually looks like. 👇
Why Multi-Terabyte Redis Deployments Are Due for a Rethink
From dragonflydb.io
591
Dragonfly
@dragonflydbio
Mar 17
we run a fuzzer on every Dragonfly PR it reads the diff, asks an LLM which edge cases to target, then spends 15 minutes hammering those exact code paths first run caught a real XPENDING off-by-one that unit tests missed full writeup by @VYavdoshenko →
Building a Self-Fuzzing CI Pipeline for Dragonfly
From dragonflydb.io
282
Dragonfly
@dragonflydbio
Mar 5
Vector search just got a serious upgrade in Dragonfly v1.37. 📈 Up to 7x higher throughput ⚡ Up to 65x lower latency If you're running RAG or high-concurrency vector workloads — this one's for you. Read the full announcement:
Dragonfly - Vector Search Just Got Faster
From dragonflydb.io
238
Dragonfly
@dragonflydbio
Feb 19
🎉 30,000 stars on GitHub! ⭐ From launch in June 2022 → 10k stars in just 75 days → 30k stars. Massive thanks to our global community of users running Dragonfly in production, contributors shaping the roadmap, and every single stargazer voting with confidence. In 2026,
345
Dragonfly
@dragonflydbio
Feb 9
Feature explosion in e-commerce machine learning? It’s an infrastructure problem. In our latest blog post, we break down how Dragonfly delivers the sub-millisecond latency and massive throughput modern feature stores demand. #ML #FeatureStore
How Dragonfly Powers Modern ML Feature Stores for E-Commerce
From dragonflydb.io
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