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Qhound
Retry, delete in bulk with precision. BullMq Made easy
Managing production queues shouldn't feel like a chore. If you’ve ever found yourself writing a one-off Node.js script just to retry 5,000 jobs that failed with a specific timeout error, Qhound was built for you. Most BullMQ dashboards are heavy web-wrappers that struggle with large datasets and lack deep filtering. We’ve rebuilt the experience from the ground up as a native desktop application to give you absolute control over your Redis queues with zero latency.
Hey Product Hunt! 👋
I’m the creator of Qhound.
As a developer at a fast-scaling startup, I’ve spent more hours than I’d like to admit staring at BullMQ dashboards. We all know the ritual: a queue gets backed up, you need to find jobs that failed with a very specific ConnectionTimeout error, and you realize your GUI can't filter them.
So, you open your code editor and start writing a one-off Node.js script just to retry or delete those specific jobs. It’s a context switch that kills productivity.
I built Qhound to be the tool I wished I had:
📌 Rust-Powered Performance: Built with Tauri and Rust, it handles thousands of jobs without the memory bloat or "stutter" of web-based dashboards.
📌 The "Script-Killer" Filter: You can filter by failedReason using Regex or exact matches. Find the error, select all, and fix them in one click.
📌 Privacy-First: Your Redis URLs stay in your system's local. No middleman, no telemetry, just a direct connection from your machine to your data.
📌 Be Organized: Organize your queues into folder.
I’m aiming to make this the gold standard for high-performance desktop queue management. I’d love to hear your feedback on the UX—especially the filtering logic!
What are the other pain points in need to tackle. Let me know in the threads! 👇
Can you save filters as presets so you can reuse them when the same error pops up again?
About Qhound on Product Hunt
“Retry, delete in bulk with precision. BullMq Made easy”
Qhound was submitted on Product Hunt and earned 6 upvotes and 3 comments, placing #74 on the daily leaderboard. Managing production queues shouldn't feel like a chore. If you’ve ever found yourself writing a one-off Node.js script just to retry 5,000 jobs that failed with a specific timeout error, Qhound was built for you. Most BullMQ dashboards are heavy web-wrappers that struggle with large datasets and lack deep filtering. We’ve rebuilt the experience from the ground up as a native desktop application to give you absolute control over your Redis queues with zero latency.
Qhound was featured in SaaS (42k followers) and Developer Tools (512.4k followers) on Product Hunt. Together, these topics include over 111.8k products, making this a competitive space to launch in.
Who hunted Qhound?
Qhound was hunted by Athithian V. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Qhound stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Athithian V