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Comment by ntoshev | Hacker News Reader

I've had an alternative Redis-like design for a while... What if you have a Python process that keeps the data in dicts and lists and Python objects as usual. These data structures get persisted to disk by forking and pickling the data as a snapshot, while the main process continues to serve requests. For a small server, the Python process can be the single-threaded web server itself (e.g. using Tornado web server).

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I did that; it was called miniredis: https://github.com/bpollack/miniredis

Your performance will be absolutely horrible compared to Redis. I can't see doing this for anything production-worthy. (Miniredis was made for a very specific use-case where the performance hit was fine--and even there, we've replaced it with the real Redis for the next version.)

I didn't exactly mean a Redis server implemented in Python instead of C... It could be that, but speaking application-specific DSL instead of generic data structure DSL.

Yes you can do this with most scripting languages. This is why I consider Redis more a DSL, proof is, it is trivial to write a Redis-complete script using a real scripting language.

However the problem with this approach is that you get a lot less performances and memory efficiency.

Redis is i/o bound, while this approach eliminates i/o and copying data from Redis to the client ;)

Not sure about memory efficiency. You can use __slots__ in Python or custom data structures (e.g. blist) if you have specific needs.

If you don't have a network interface, is not the same thing as Redis. Even Redis can be written as a C library, but it's not the same. Redis is all about a shared persistent state.

I've no idea about __slots__, just a feeling that there are too much underscores to work well ;) But in general to get as memory efficient as Redis in a scripting language is very hard for different (good) reasons.

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