Hi everyone, first of all sorry my english :), this is my first email in this
mainlist.
My name is Jan Palach I'm from Brazil and i'm novice in SQLALchemy
ecosystem. I'm testing the combination PostgreSQL + SQLAlchemy(using psycopg2)
and CPython 2.x, to create a database layer for backend applications that
process a large amount of data(internal's policies questions impossibility the
NoSQL uses, and we need the flexibility of ORM to choice different databases
for different environments). Well, I have the following picture(for test only):
- A windows 8 machine with PostgreSQL 9.2.3: There is a table mob.t_test with
the following structure:
- CUSTOMER_ID character 32
- ID SERIAL
- NAME character 64
- There is an index for name, id and customer_id.
- The database is listen for external connections through the local network.
- A OSX Mountain Lion Macbook Pro running scripts for test inserts in the
remote database above.
I ran some experiments with two difference scripts, because I need to choose
which technology w'll use for the future.
For insert 100k lines i got the following results:
SCRIPT01[1]: Average ~17 seconds per iteration.
SCRIPT02[2]: Average ~10 minutes per iteration.
For insert 500 lines i got the following results:
SCRIPT01[1]: Average ~0.1 seconds per iteration.
SCRIPT02[2]: Average ~7 seconds per iteration.
I now that ORM add some overhead, but I believe that I'm making something
wrong. Do you help me to identify something to improve it, without losing
different databases flexibility?
1 - http://pastebin.com/62VppSH4
2 - http://pastebin.com/MHdc7AGx
Thanks.
Att,
Jan Palach
--------------
See my linkedin: http://www.linkedin.com/pub/jan-palach/16/b1a/7a3
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