LightAdmin speeds application development by bringing a pluggable, fully operational data management backend to JPA-based applications and relieving your codebase for more important things. It allows developers to define a data management backend with POJOs and JPA and customize it using simple Domain-specific language.
DataNucleus AccessPlatform is a standards-compliant Java persistence product. It is fully compliant with the JDO1, JDO2, JDO2.1, JDO2.2, JDO3, JPA1, JPA2 and JPA2.1 Java standards, and provides a REST API. It complies with the OGC Simple Feature Spec for persistence of geospatial Java types. It allows access to all popular RDBMS available today, together with the MongoDB, LDAP, NeoDatis, JSON, Excel/ODF spreadsheets, XML, BigTable, HBase, and Neo4j databases.
KeyBox is a Web-based SSH console for executing commands and managing multiple systems simultaneously. It allows you to share terminal commands and upload files to all your systems. Once the sessions have been opened you can select a single system or any combination on which to run your commands. Also, additional system administrators can be added and their terminal sessions and history can be audited.
mrtparse is a module to read and analyze the MRT data format. The MRT format can be used to export routing protocol messages, state changes, and routing information base contents, and is standardized in RFC6396. Programs like Quagga/Zebra, BIRD, OpenBGPD, and PyRT can dump to MRT.
Piggydb is a flexible and scalable knowledge building platform that supports a heuristic or bottom-up approach to discover new concepts or ideas based on your input. You can begin with using it as a flexible outliner, diary or notebook, and as your database grows, Piggydb helps you to shape or elaborate your own knowledge. Piggydb is a Web application provided as a self-contained package that contains a Web server and database engine.
Duke is a fast and flexible record linkage engine. It does not use the traditional blocking (sort by key) approach, but instead relies on Lucene. This makes it high-performance (able to process 1,000,000 records in ~10 minutes). Duke can be run from the command line, but also has an API allowing incremental linking applications to be built easily. It supports reading data from CSV, JDBC, SPARQL, and NTriples, and also supports a number of string comparators and string normalizers.