Hey Product Hunt family!

We love fast hardware. Modern NVMe SSDs are absolute beasts, capable of processing millions of operations per second. But there s a catch: traditional databases are holding them back. Old databases rely on legacy code that creates massive digital traffic jams, making your ultra-fast storage sit idle while your CPU wastes time.

So, we built VeltrixDB a next-gen Key-Value store built from scratch to do one thing: destroy performance bottlenecks and unlock the true physical speed of your hardware.

Hey Product Hunt!

Almost every popular database today is doing something behind the scenes that wastes your server power and slows down your app: They are constantly sorting data on disk.

This made sense 10 years ago when hard drives were slow. But today? Modern NVMe SSDs are incredibly fast. Forcing them to sort data using old methods is literally like putting speed bumps on an F1 racing track.

So, we asked a very simple question: What happens if we just... stop sorting data?

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.

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!