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A fast JSON parser and generator optimized for statistical data and the web. Started out as a fork of RJSONIO, but has been completely rewritten in recent versions. The package offers flexible, robust, high performance tools for working with JSON in R and is particularly powerful for building pipelines and interacting with web APIs. The implementation is based on the mapping described in the vignette of the package (Ooms, 2014). In addition to drop-in replacements for toJSON and fromJSON, jsonlite contains functions to stream, validate, and prettify JSON data. The unit tests included with the package verify that all edge cases are encoded and decoded consistently for use with dynamic data in systems and applications.

With Glom you can design table definitions and the relationships between them, plus arrange the fields on the screen. You can edit and search the data in those tables, and specify field values in terms of other fields. It's as easy as it should be. The design is loosely based on FileMaker Pro, with the added advantage of separation between interface and data. Its simple framework should be enough to implement most database applications. Without Glom these systems normally consist of lots of repetitive, unmaintainable code. Glom-specific data such as the relationship definitions is saved in the Glom document. Glom re-connects to the database server when it loads a previous Glom document. The document is in XML format. Glom uses the PostgreSQL database backend but it can not edit databases that it did not create, because it uses only a simple subset of Postgres functionality.

hamsterdb is a lightweight embedded database engine. It is in development for more than three years and concentrates on ease of use, high performance, stability and portability. The hamsterdb API is simple and self-documenting. The interface is similar to other widely-used database engines. Fast algorithms and data structures guarantee high performance for all scenarios. Hamsterdb has hundreds of unittests with a test coverage of over 90%. Each release is tested with thousands of acceptance tests in many different configurations, tested on up to six different hardware architectures and operating systems. Written in plain ANSI-C, hamsterdb runs on many architectures: Intel-compatible (x86, x64), PowerPC, SPARC, ARM, RISC and others. Tested operating systems include Microsoft Windows, Microsoft Windows CE, Linux, SunOS and other Unices.

JDB is a package of commands for manipulating flat-ASCII databases from shell scripts. JDB is useful to process medium amounts of data (with very little data you'd do it by hand, with megabytes you might want a real database). JDB is very good at doing things like: * extracting measurements from experimental output * re-examining data to address different hypotheses * joining data from different experiments * eliminating/detecting outliers * computing statistics on data (mean, confidence intervals, histograms, correlations) * reformatting data for graphing programs Rather than hand-code scripts to do each special case, JDB provides higher-level functions. JDB is built on flat-ASCII databases. By storing data in simple text files and processing it with pipelines it is easy to experiment (in the shell) and look at the output.

JRobin is a 100% pure java implementation of RRDTool's functionality. It follows the same logic and uses the same data sources, archive types and definitions as RRDTool does. JRobin supports all standard operations on Round Robin Database (RRD) files: CREATE, UPDATE, FETCH, LAST, DUMP, XPORT and GRAPH. JRobin's API is made for those who are familiar with RRDTool's concepts and logic, but prefer to work with pure java. If you provide the same data to RRDTool and JRobin, you will get exactly the same results and graphs. JRobin is made from the scratch and it uses very limited portions of RRDTool's original source code. JRobin does not use native functions and libraries, has no Runtime.exec() calls and does not require RRDTool to be present. JRobin is distributed as a software library (jar files) and comes with full java source code (LGPL licence).

Because the many-to-many relationships are not real relationships, they can not be introspected with DBIx::Class. Many-to-many relationships are actually just a collection of convenience methods installed to bridge two relationships. This DBIx::Class component can be used to store all relevant information about these non-relationships so they can later be introspected and examined. This module is fairly esoteric and, unless you are dynamically creating something out of a DBIC Schema, is probably the wrong solution for whatever it is you are trying to do. Please be advised that compatibility is not guaranteed for DBIx::Class 0.09000+. We will try to mantain all compatibility, but internal changes might make it impossible.

This is the port for all stuff that comes in the contrib subtree of the postgresql distribution. This subtree contains porting tools, analysis utilities, and plug-in features that are not part of the core PostgreSQL system, mainly because they address a limited audience or are too experimental to be part of the main source tree. This does not preclude their usefulness. Each subdirectory contains a README file with information about the module. Some directories supply new user-defined functions, operators, or types. After you have installed the files you need to register the new entities in the database system by running the commands in the supplied .sql file. For example, $ psql -d dbname -f module.sql The .sql files are installed into /usr/local/share/postgresql/contrib For more information, please see /usr/local/share/doc/postgresql/contrib/README* This software is part of the standard PostgreSQL distribution.

This is the port for all stuff that comes in the contrib subtree of the postgresql distribution. This subtree contains porting tools, analysis utilities, and plug-in features that are not part of the core PostgreSQL system, mainly because they address a limited audience or are too experimental to be part of the main source tree. This does not preclude their usefulness. Each subdirectory contains a README file with information about the module. Some directories supply new user-defined functions, operators, or types. After you have installed the files you need to register the new entities in the database system by running the commands in the supplied .sql file. For example, $ psql -d dbname -f module.sql The .sql files are installed into /usr/local/share/postgresql/contrib For more information, please see /usr/local/share/doc/postgresql/contrib/README* This software is part of the standard PostgreSQL distribution.

This is the port for all stuff that comes in the contrib subtree of the postgresql distribution. This subtree contains porting tools, analysis utilities, and plug-in features that are not part of the core PostgreSQL system, mainly because they address a limited audience or are too experimental to be part of the main source tree. This does not preclude their usefulness. Each subdirectory contains a README file with information about the module. Some directories supply new user-defined functions, operators, or types. After you have installed the files you need to register the new entities in the database system by running the commands in the supplied .sql file. For example, $ psql -d dbname -f module.sql The .sql files are installed into /usr/local/share/postgresql/contrib For more information, please see /usr/local/share/doc/postgresql/contrib/README* This software is part of the standard PostgreSQL distribution.

This is the port for all stuff that comes in the contrib subtree of the postgresql distribution. This subtree contains porting tools, analysis utilities, and plug-in features that are not part of the core PostgreSQL system, mainly because they address a limited audience or are too experimental to be part of the main source tree. This does not preclude their usefulness. Each subdirectory contains a README file with information about the module. Some directories supply new user-defined functions, operators, or types. After you have installed the files you need to register the new entities in the database system by running the commands in the supplied .sql file. For example, $ psql -d dbname -f module.sql The .sql files are installed into /usr/local/share/postgresql/contrib For more information, please see /usr/local/share/doc/postgresql/contrib/README* This software is part of the standard PostgreSQL distribution.