MUSCLE (Multi User Server Client Linking Environment) is an N-way messaging server and networking API. It includes client-side networking APIs for various languages, including C, C++, C#, Delphi, Java, and Python. MUSCLE lets programs communicate over a network via streams of serialized Message objects. The included server program ("muscled") lets its clients message each other and store information in its server-side hierarchical database. The database supports flexible queries via hierarchical wildcarding, and "live" updates via a subscription mechanism.
mysqlblasy is a Perl script for automating MySQL database backups. It uses "mysqldump" for dumping mysql databases to the files sytem. It was written with automated usage in mind. For example, it is silent during operation, and only produces noise on errors/problems. It rotates backups automatically to prevent the backup disk from getting full when the administrator is on vacation (or is lazy).
radlib is a C language library developed to abstract details of interprocess communications and common Linux/Unix system facilities so that application developers can concentrate on application solutions. It encourages developers to use a proven paradigm of event-driven, asynchronous design. By abstracting interprocess messaging, events, timers, and any I/O device that can be represented as a file descriptor, radlib simplifies the implementation of multi-purpose processes, as well as multi-process applications. In short, radlib is a sincere attempt to provide real-time OS capability on a non-real-time OS.
The TREE Data Server captures real-time financial data from one or several data feed services (e.g. IB TWS API), archives data in a historical database, and makes both live and archived data available to client applications. The system can be used in real-time charting, an ATS, a tick feed simulator, or any situation in which multiple clients need real-time access to the tick stream or archived tick data. In addition, the archived tick stream and tick data are available for offline data analysis and backtesting.