On Sun, Oct 24, 2010 at 12:38 PM, dbb wrote:
> My question is : since web2py is a powerful simple framework, can it
> simplify daytona? I have no more information about daytona, they said
> the firm that developed it has placed it as an open source, but not
> sure. Daytona is a very powerful database that can store billions of
> rows of data; they said: you stop using daytona when you ran out of
> space ( hardware), or when you do not have any more data to store. For
> web2py supporting daytona will give it a high visibility. Debebe
Question here is what kind of app would need to scale THAT much?
Reading the overview:
"The 64 CPU (SMP) partition houses 6 largish Daytona tables of call
detail data. As of Sept 14, 2005, the largest one of these tables
contained 743 billion records whose average (compressed) length was
52.2 bytes. This 52.2 bytes uncompresses on average to a uncompressed
format measuring 216 bytes, implying an expansion factor of 4:1 .
(This uncompressed format is essentially a human-readable ASCII
format.) This compressed table takes up 38.8 terabytes; clearly it is
much better to buy 38.8 terabytes of disk than 159 terabytes. In all,
this partition contains 1.026 trillion records. (FYI, all terabytes
here are 1024 based.) "
I seriously doubt most people have access to such hardware, let alone
that amount of data. For most practical purposes Postgres, Couch, et
al. will scale very well, especially if you scale horizontally. By the
time you reach a point where you start considering Daytona, you'd
probably be converting all your backend code to Erlang+C anyway. :)
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