Flexible Schemas with PostgreSQL and Elasticsearch

2018 Dec26

R
elational Databases typically make use of a rigid schema - predefined tables containing typed columns allowing for a rich set of functionality that would otherwise be impossible. It is both a major strength as well as a major weakness. On one hand strong typing allows databases to expose a rich set of operators, functions and functionality for each of the types. For postgres, this usually presents itself in the form of column types sql syntax to interact with them. On the other hand it means that all of the data in the table is uniform and deviations or alterations are rather difficult to do.

At the day job, I am in the process of migrating a number of applications

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filed under:  postgres elasticsearch json

Handling Large Files With NodeJS and Elastic Search

2012 Apr12
S

o consider myself to be an equal opportunity coder. I like investigating different tools built in different languages to solve different types of problems. Recently at work I had the opportunity to play around with [elasticsearch](http://www.elasticsearch.org). Elasticsearch brings the whole distributed / non relational data craze to the world of search. It is actually a rather impressive piece of tech. If you are at all interested in search as a problem, I recommend you give it a look. In any event, I need to get some data into the search engine to play around with. Where could I get a good deal of data without doing the heavy lifting myself? Twitter! Sure the twitter activity stream.

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filed under:  csv python elasticsearch io json node