Case Study: Boosting Performance and Cutting Cost with Laravel Queues
Discover how Dragonfly customer Inspector overcame scaling challenges in their Laravel queue management and significantly reduced cloud costs by switching to Dragonfly.
Deliver Millions of Jobs Without Failures
DragonflyDB delivers concurrent jobs faster with fewer retries and no cluster overhead, so your real-time apps and ML workflows stay responsive at peak demand.
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Message Queues That Scale Under Pressure
Process jobs instantly, no matter the traffic load.
Message queues are the backbone of critical systems—from email delivery to fraud detection to ML scoring. But under load, they often become bottlenecks. Throughput drops, retries pile up, and latency spikes. As concurrency rises, memory gets overwhelmed, making it harder to scale. These aren’t rare edge cases—they’re real production problems. Real-time AI/ML workloads need queues built for high concurrency and throughput to keep jobs flowing and prevent backlogs at peak demand.
DragonflyDB
DragonflyDB
High-Throughput, Low-Failure Queues for Real-Time Workloads
DragonflyDB delivers consistent low-latency performance, even during peak load, without the need for sharding, manual tuning, or job balancing. It eliminates delays, retries, and job failures that often plague message queues under heavy traffic or high concurrency. With the ability to process over 8 million queue operations per second at sub-millisecond latency, DragonflyDB remains stable during 10x traffic surges.
It integrates seamlessly into your existing architecture with zero code changes and no complex migrations. Compatible with popular frameworks like BullMQ, Sidekiq, and Celery, DragonflyDB allows teams to move quickly without adding operational overhead. Whether powering real-time features, backend processing, or ML pipelines, DragonflyDB ensures jobs are delivered reliably and on time, keeping your applications responsive and your systems scalable with confidence.
Convert Queue Performance into Business-Critical Reliability
Protect Revenue and Risk-Sensitive Workflows
DragonflyDB’s multi-threaded architecture keeps queue latency under 1ms even during 10x spikes. This ensures critical workflows like bet placements, fraud checks, and pricing updates run without delays thus protecting revenue and user trust when every second counts.
Automatically handle Customer Demand Surges
Whether it's a flash promotion or a major live event, DragonflyDB’s built-in memory-safe design prevents crashes and processes over 8 million queue ops/sec, without tuning or clusters, so real-time applications stay responsive, even when demand unexpectedly surges.
Accelerate Product Velocity
Unlike Redis, DragonflyDB eliminates the need for queue tuning, rebalancing, or constant monitoring, so engineers don’t waste time chasing stuck jobs or firefighting traffic spikes. With fewer disruptions, teams ship faster and report spending up to 60% less time on queue maintenance.
“I really can’t say enough, DragonflyDB exceeded my expectations. The usage is low, the load is low, and everything is just wired perfectly in the system.”
Ray Hughes
Co-Founder & CTO at Sharp App
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