Pushing and Polling Data Differences in Approach on the Gnip platform

Obviously we have some understanding on the concepts of pushing and polling of data from service endpoints since we basically founded a company on the premise that the world needed a middleware push data service.    Over the last year we have had a lot of success with the push model, but we also learned that for many reasons we also need to work with services via a polling approach.   For this reason our latest v2.1 includes the Gnip Service Polling feature so that we can work with any service using push, poll or a mixed approach.

Now, the really great thing for users of the Gnip platform is that how Gnip collects data is mostly abstracted away.   Every end user developer or company has the option to tell Gnip where to push data that you have set up filters or have a subscription.   We also realize not everyone has an IT setup to handle push so we have always provided the option for HTTP GET support that lets people grab data from a Gnip generated URL for your filters.

One place where the way Gnip collects data can make a difference, at this time, for our users is the expected latency of data.  Latency here refers to the time between the activity happening (i.e. Bob posted a photo, Susie made a comment, etc) and the time it hits the Gnip platform to be delivered to our awaiting users.     Here are some basic expectation setting thoughts.

PUSH services: When we have push services the latency experience is usually under 60 seconds, but we know that this is not always the case sense sometimes the services can back-up during heavy usage and latency can spike to minutes or even hours.   Still, when the services that push to us are running normal it is reasonable to expect 60 second latency or better and this is consistent for both the Community and Standard Edition of the Gnip platform.

POLLED services:   When Gnip is using our polling service to collect data the latency can vary from service to service based on a few factors

a) How often we hit an endpoint (say 5 times per second)

b) How many rules we have to schedule for execution against the endpoint (say over 70 million on YouTube)

c) How often we execute a specific rule (i.e. every 10 minutes).     Right now with the Community edition of the Gnip platform we are setting rule execution by default at 10 minute intervals and people need to have this in mind with their expectation for data flow from any given publisher.

Expectations for POLLING in the Community Edition: So I am sure some people who just read the above stopped and said “Why 10 minutes?”  Well we chose to focus on “breadth of data ” as the initial use case for polling.   Also, the 10 minute interval is for the Community edition (aka: the free version).   We have the complete ability to turn the dial and use the smarts built into the polling service feature we can execute the right rules faster (i.e. every 60 seconds or faster for popular terms and every 10, 20, etc minutes or more for less popular ones).    The key issue here is that for very prolific posting people or very common keyword rules (i.e. “obama”, “http”, “google”) there can be more posts that exist in the 10 minute default time-frame then we can collect in a single poll from the service endpoint.

For now the default expectation for our Community edition platform users should be a 10 minute execution interval for all rules when using any data publisher that is polled, which is consistent with the experience during our v2.1 Beta.    If your project or company needs something a bit more snappy with the data publishers that are polled then contact us at info@gnip.com or contact me directly at shane@gnip.com as these use cases require the Standard Edition of the Gnip platform.

Current pushed services on the platform include:  WordPress, Identi.ca, Intense Debate, Twitter, Seesmic,  Digg, and Delicious

Current polled services on the platform include:   Clipmarks, Dailymotion, deviantART, diigo, Flickr, Flixster, Fotolog, Friendfeed, Gamespot, Hulu, iLike, Multiply, Photobucket, Plurk, reddit, SlideShare, Smugmug, StumbleUpon, Tumblr, Vimeo, Webshots, Xanga, and YouTube

New Gnip schema live on demo.gnip.com

We have flipped the switch to allow people to start working with our new schema at http://demo.gnip.com. In addition to standing up the site with the updated schema we have moved over all the existing accounts from the current system, so your existing gnipcentral.com user and password also get you access to the demo system.

The following publishers are in the demo system and we plan to add more over the course of the next month during the beta period.

  • Digg
  • Identi.ca
  • Seesmic
  • Six Apart
  • Twitter

We will be posting additional examples of how we mapped these social media services to the updated Gnip Schema in the Gnip Community and will link to those examples from the blog as well as point to them in our standard release newsletter that will go out later today.

Based on the feedback we have received there is a lot of interest in the enhanced metadata in the new schema that can be used to support additional types of  URLs, multiple tags, geo data, and rich media. Now, go grab some data and do something cool with it.

More Examples of How Companies are Using Gnip

We have noticed that we are interacting with two distinct groups of companies; those who instantly understand what Gnip does and those that struggle with what we do, so we decided to provide a few detailed real-world examples of the companies we are actively working with to provide data integration and messaging services today.

First, we are not an end-user facing social aggregation application. (We repeat this often.) We see a lot of people wanting to put Gnip in that bucket along with social content aggregators like FriendFeed, Plaxo and many others. These content aggregators are destination web sites that provide utility to end users by giving them flexibility to bring their social graph or part of their graph together in one place. Also, many of these services are now providing web APIs that allow people to use an alternative client to interact with their core services around status updates and conversations as well other features specific to the service.

Gnip is an infrastructure service and specifically we provide an extensible messaging system that allows companies to more easily access, filter and integrate data from web based APIs. While someone could use Gnip as a way to bring content into a personal social media client they want to write for a specific social aggregator it is not something we are focused. Below are the company use cases we are focused:

  1. Social content aggregators: One of the main reasons we started Gnip was to solve the problems being caused by the point-to-point integration issues that were springing up with the increase of user generated content and corresponding open web APIs. We believe that any developer who has written a poller once, twice, or to their nth API will tell you how unproductive it is to write and maintain this code. However, writing one-off pollers has become a necessary evil for many companies since the content aggregators need to provide access to as many external services as possible for their end users. Plaxo, who recently integrated to Gnip as a way to support their Plaxo Pulse feature is a perfect example, as are several other companies.
  2. Business specific applications: Another main reason we started Gnip was that we believe more and more companies are seeing the value of integrating business and social data as a way to add additional compelling value to their own applications. There are a very wide set of examples, such as how Eventvue uses Gnip as a way to integrate Twitter streams into their online conference community solution, and the companies we have talked to about how they can use Gnip to integrate web-based data to power everything from sales dashboards to customer service portals.
  3. Content producers: Today, Gnip offers value to content producers by providing developers an alternative tool that can be used to integrate to their web APIs. We are working with many producers, such as Digg, Delicious, Identi.ca, and Twitter, and plan to continue to grow the producers available aggressively. The benefits that producers see from working with Gnip include off-loading direct traffic to their web apis as well as providing another channel to make their content available. We are also working very hard to add new capabilities for producers, which includes plans to provide more detailed analytics on how their data is consumed and evaluating publishing features that could allow producers to define their own filters and target service endpoints and web sites where they want to push relevant data for their own business needs.
  4. Market and brand research companies: We are working with several companies that provide market research and brand analysis. These companies see Gnip as an easy way to aggregate social media data to be included in their brand and market analysis client services.

Hopefully this set of company profiles helps provide more context on the areas we are focused and the typical companies we are working with everyday. If your company does something that does not fit in these four areas and is using our services please send me a note.

Web APIs of All Shapes and Sizes

Not all APIs have the same capabilities and therefore they provide different levels of access to events, procedures and data. Seems obvious, but you would not think that based on the normal questions we see from people. In fact we have found that APIs can be like a lot like apples and oranges. So, with the number of available APIs growing, at a rate that can be more than 60 per month we thought people would benefit from some simple way to think of API categorization based on how they expose events and data.

We work with a large variety of APIs from a variety of service providers and have noticed that most APIs fall into a few descriptive types based on how they expose events and data. The following are the main ways we are starting to look at APIs.

  • Fire hose or “full stream”. Identi.ca and Twitter are two examples, but Flickr also has a fire hose
  • User-based stream: These services do not directly expose a full stream, but instead give people a way to assemble an aggregate stream based on a list of users. Flickr again is a good example and there are many others.
  • Activity-based Tag-based and “other”: The main way to work with these services is usually some defined activity (tag, bookmark, etc) access to information or pre-defined streams based on feeds. An example would be Delicious, which allows multiple methods to access information by APIs and feeds.

This bi-frication in API types is something people should keep in mind when they want to access a service for some specific need. If you need to get events and data for a specific need then obviously the behavior of the API is going to impact your approach. And of course here at Gnip we are hard at work trying to provide consistent approaches across all types of APIs, so back to work!