SqliteJdbcNG is a JDBC driver for SQLite. The overall goal of this project is to start a fresh implementation that leverages newly available technologies in the Java world. For example, any SQLite driver for any language must integrate with the native SQLite library. All of the current Java implementations rely on a custom JNI library to call out to the SQLite library. This extra layer can easily create a headache for the development and deployment of the driver, since it needs to be built for a variety of operating systems. Fortunately, there are technologies like Bridj and JNA that can be used to call native code directly from Java. By leaving the majority of the headaches of integrating with the native library to the Bridj project, more time can be spent on making a high quality driver that is more compliant with the JDBC4 spec.
MLPACK is a C++ machine learning library with an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. It contains algorithms such as k-means, Gaussian mixture models, hidden Markov models, density estimation trees, kernel PCA, locality-sensitive hashing, sparse coding, linear regression and least-angle regression.
ClodHopper is a Java library for high-performance clustering of numerical data. It contains clustering implementations such as K-Means, K-Means++, X-Means, G-Means, Fuzzy C-Means, Jarvis-Patrick, and various forms of hierarchical clustering. ClodHopper's clustering implementations take advantage of the host system's concurrent processing ability to speed clustering. The data structures are also very lean to conserve memory usage. ClodHopper is very extensible. If you are developing a new clustering algorithm, you may save yourself an enormous amount of work by extending a ClodHopper base class.
Hatteras is a business events subscription engine which makes up one component of the Fogcutter Suite. It works with Quoddy to provide the ability for users to create subscriptions to business events on the organization's ESB infrastructure. It connects to Quoddy, downloads all defined subscriptions, then listens for matching messages. Messages which match a subscription are persisted to an XML database, and Hatteras then sends a notification to Quoddy which creates a subscription item record which can be rendered in the user's stream. Quoddy and Hatteras thereby provide seamless access to important business events, alongside other import pieces of content the user has selected.