Google Cloud SQL is web service that allows you to create, configure, and use relational databases with your App Engine applications. It is a fully-managed service that maintains, manages, and administers your databases, allowing you to focus on your applications and services.

By offering the capabilities of a MySQL database, the service enables you to easily move your data, applications, and services into and out of the cloud. This allows for high data portability and helps in faster time-to-market because you can quickly leverage your existing database (using JDBC and/or DB-API) in your App Engine application.

Historically, getting the right predictive model has required detailed knowledge of algorithmic behavior and experience with similar datasets, and a lot of guess-and-check. With the Prediction API, we ask you what behavior you want to see, and search across many algorithms to find the best-matching one.

This small tag, that is included in the head of your application will signal to the browser the intention to handle a “share” action for a selection of URI’s (think “share this page”), and will register it in the system so that the user can choose it when a client application wants to provide “share” functionality in their app.

This article now builds on the premise that you are convinced that a public API will help your already available service. The article now discusses important points that you must consider before you embark on coding out the public API. Each of these points focuses on a theme rather than the implementation details and they are listed in no particular order of importance.

The Prediction API enables quick and easy automation of repetitive tasks. It accesses Google's machine learning algorithms to analyze your historic data and predict likely future outcomes. Upload your data to Google Storage for Developers, then use the Prediction API to make real-time decisions in your applications. The Prediction API implements supervised learning algorithms as a RESTful web service to let you leverage patterns in your data, providing more relevant information to your users. Run your predictions on Google's infrastructure and scale effortlessly as your data grows in size and complexity.

The Ident Engine is part of a year long personal project into combining social graph data with other open data sources. With over 1.3 billion hCard profiles on the web and RDF growing in strength, the semantic web has reached a tipping point. I built the Ident Engine to show that constructing user experiences by blending semantic web APIs and other open data sources is not only practical, but offers exciting opportunities.

If you want to get your hands on the best MTV, VH1, CMT and Logo have to offer, you need the MTV Networks Content API. This is the place to find the documentation and information needed to start using it right away.

Modest Maps is a BSD-licensed display and interaction library for tile-based maps in Flash (ActionScript 2.0 and ActionScript 3.0) and Python.

Spread is an open source toolkit that provides a high performance messaging service that is resilient to faults across local and wide area networks. Spread functions as a unified message bus for distributed applications, and provides highly tuned application-level multicast, group communication, and point to point support. Spread services range from reliable messaging to fully ordered messages with delivery guarantees.