Shubham sharma's profile on Product Hunt

About

I’m a Senior Platform & Distributed Systems Engineer with 12+ years of experience building scalable, resilient, and high-performance systems across cloud, data, and infrastructure domains. My expertise spans real-time streaming architectures, cloud-native platforms, observability, DevOps automation, and large-scale distributed systems. Over the years, I’ve designed and operated mission-critical platforms on both AWS and GCP, handling high-throughput data pipelines, low-latency event streaming, infrastructure automation, and production-grade Kubernetes ecosystems. I enjoy solving complex engineering challenges related to scalability, reliability, performance optimization, and system resilience.

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Maker History

VeltrixDBZero-compaction, memory-first NVMe key-value storage engine
May 2026

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Joined Product HuntMay 23rd, 2026

Forums

p/veltrixdb

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1d ago

1 Billion keys with 500µs P99 latency. Here is why we completely stopped sorting data on disk.

Hey Product Hunt!

If you ve ever scaled a traditional Key-Value store (like RocksDB or LevelDB), you already know the pain of the "Compaction Death Spiral." You write a 1KB value, but your storage engine rewrites it 10 to 30 times in the background just to keep things sorted. Eventually, your disks choke, your CPU spikes, and your P99 latency goes completely off the charts.

p/veltrixdb

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6d ago

Are LSM-trees actually holding back modern NVMe hardware?

Hi makers! I ve been obsessed with storage performance lately. We keep buying 7GB/s NVMe drives, but most databases still use architecture (like LSM-trees) designed for a time when disks were the bottleneck.

Background compactions, write-amplification spikes, and P99 latency jitters seem to be the "tax" we pay for general-purpose storage. Is it time we move toward memory-first, zero-compaction engines, even if it means trading off some RAM? Or is the LSM-tree still the king of the hill? Would love to hear from anyone fighting database latency at scale!

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3d ago

VeltrixDB - Zero-compaction, memory-first NVMe key-value storage engine

VeltrixDB: High-Performance KV Storage We built VeltrixDB for bare-metal NVMe. By ditching LSM-trees for an In-memory Adaptive Radix Tree (ART) and append-only Value Log, we’ve eliminated compaction spikes. Stack: Linux io_uring + Direct I/O. Performance: Flat, microsecond latencies at billion-key scale. Trade-off: Optimized for pure IOPS & lock-free point reads (No range queries). Perfect for HFT, AdTech & extreme caching. Benchmarks: https://github.com/VeltrixDB/vel...

Shubham sharma