[avinassh]

> Skytable's primary goal is performance and scale. Even with a query language it can outperform K/V stores which use simple commands (benchmarks will be shared in another post).

How does Skytable achieves this? In other words, what makes it different than others?

[sayann]

The linked blog post has some notes on the architectural differences. Overall, we use fundamentally different underlying implementations for various components, from the network layer to the storage engine.

If you want a more in-depth review you can read https://docs.skytable.io/architecture

That document will be updated frequently!

[avinassh]

I skimmed through the article, still I don’t get it what makes it so fast that it can beat other KV Stores.

Does it use a B Tree / LSM / Bitcask? Or something else entirely?

How does your storage engine compare with sled?

The storage section also mentioned that most data stays in RAM and it is planned to change. Is it still the same? The benchmarks were ran on the in-memory version or disk one (if that is changed)

Also, can you share against which all KV Stores the benchmark was done?

The project looks very exciting and I’d love to know more details

[sayann]

Skytable is currently primarily in-memory (which is to change soon; approximately Q1 next year). The storage engine actually uses various drivers and most of them are AOF-style custom implementations.

Real-time/background compaction and more will be implemented shortly before GA is shipped (this is currently a beta).