Gnip Standardizes and Reduces Strain on Facebook APIs
Today, social media API aggregator Gnip is improving how it combines different Facebook API feeds into one output stream. It now includes various public Page-based APIs alongside the keyword search API it integrated after f8, with the intention of helping developers access Facebook data more quickly and easily.
The change strengthens Gnip’s brand management service which allows users to monitor keywords across all publicly posted Facebook objects and stay aware of changes to certain Pages without constantly making API calls.
Gnip acts as a proxy between content publishers like Facebook and Flickr, and services that utilize API data, like FriendFeed and Plaxo. Normally, these data consumers would have to expend resources writing and maintaining code to interface with each publisher’s APIs. Then, to keep their own sites up-to-date, they’d have to incessantly query each API to occasionally find a change, such as a new photo being uploaded. Gnip simplifies this process by standardizing many of the most popular APIs so developers only have to support the one overarching Gnip API. Then whenever data changes on the publisher’s site, it notifies Gnip, which then pushes the data to the consuming service, eliminating needless API calls. For a more technical walkthrough of API aggregators, see TechCrunch IT’s in-depth guide to Gnip.
Gnip lets users quickly choose which content providers they want API feeds from and what data they want to pull. It then displays a visual dashboard for monitoring the API pulls, allowing users to quickly diagnose any problems with data collection. For example, a user could now set Gnip to push them data whenever a new Page with their brand name in the title is created, allowing them to stay aware of any protest Pages that spring up. Gnip’s services range in price from $200 per month for a non-production sandbox to $2,000 per month for enterprise. Facebook stands to gain from wider adoption of aggregators like Gnip, as decreasing extraneous API queries increases API speeds and prevents delays which have previously slowed developer adoption.