Here's a brief rundown of AidData's technical architecture and guidelines. This will be particularly useful for technologists, software developers, and data visualizers/analysts who want to interact with our API, related services and/or data.
Guidelines of AidData andTechnical Architecture
AidData's API is a RESTful API, built in NodeJS. Our database engine is MongoDB, but most of the query work is done by Elastic Search.
This combination of document oriented database plus an Apache Lucene-based search engine gives us the flexibility needed to handle a variety of requests while still maintaing very good performance.
Applications should receive input as a feed (json), i.e. our API or other feed, or by file. See our research releases for downloadable files.
Apps should preferably run visualizations directly from one of our feeds (json) to allow for future format changes or updates to the data
If you do decide to store data on a local database preferably use MongoDB, but MySQL and PostgreSQL also work. Just be aware that storing data on a local database means you either have to continually refresh the data or risk having outdated information in your application