i wrote about why i thought citus was the best a week ago: http://blog.faraday.io/3-reasons-citus-is-best-non-heroku-po...

Faraday - Burlington, VT (Vermont) - ONSITE

Backend engineer

Help build the next generation of marketing with Node, Ruby, Postgres 9.4+, PostGIS 2.1+, Docker, ECS, Vault, and other cutting edge tech.

cto@faraday.io

I cache with redis:

https://github.com/seamusabshere/lock_and_cache

(and lock too, with Redis Redlock)

best. hn. ever.

Recommended by Oleg Bartunov in http://www.postgresql.org/message-id/CAF4Au4y93AV2dKuQ2ABJbs...

* API client with batching and parallelization built in (100 queries in a single request, multiple requests run in parallel, etc.)

* robustness in the face of bad street suffixes (for example, in Burlington, VT, you may find data with "CR" meaning "CIRCLE" instead of the official USPS "CREEK")

* fuzzy street name matching (PAKCER -> PACKER)

* accurate geocoding in rural United States

* fuzzy international place matching (like "ST PANCRAS ST STATION" in London)

In your experience is the rural US geocoding problem a software problem or a lack of underlying data?

You can get predicted columns via https://github.com/no0p/alps ... Turns out that adding words like infer to the lex is kind of a big project in pgsql. Excellent work with the language aspect of it in BayesDB -- well thought out.

thanks for the tip! it was worth the karma i lost for my attempt at humor...

love it

thank you for sharing!

ok, i'll go first: i love https://github.com/seamusabshere/upsert because it seems like a new idea and https://github.com/seamusabshere/fuzzy_match because it feels like i've combined string similarity and array enumeration to make something truly useful.