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Regular Statement String (RSS) provides several libraries in C, Java, and COM to implement and demonstrate the key-value development method using well-designed "strings" (RSS) as the media. Regular Statement String also shows a way to write "Process Oriented" applications.
Enhancements:
- This release adds an implementation for SUN Solaris (SPARC).

SQL::Statement::Embed can embed a SQL engine in a DBD or module.

SQL::Statement is designed to be easy to embed in other modules and to be especially easy to embed in DBI drivers. It provides a SQL Engine and the other module needs to then provide a data source and a storage mechanism. For example, the DBD::CSV module uses SQL::Statement as an embedded SQL engine by implementing a file-based data source and by using DBI as the user interface. Similarly DBD::Amazon uses SQL::Statement as its SQL engine, provides its own extensions to the supported SQL syntax, and uses on-the-fly searches of Amazon.com as its data source.

SQL::Statement is the basis for eight existing DBDs (DBI database drivers). If you have a new data source, you too can create a DBD without having to reinvent the SQL wheel. Its fun, its easy, become a DBD author today!

SQL::Statement can be also be embedded without DBI. Well explore that first since developing a DBD uses most of the same methods and techniques.

The role of SQL::Statement subclasses

SQL::Statement provides a SQL parsing and execution engine. It does not provide a data source or storage mechanism other than in-memory tables. The DBD::File module is a subclass of SQL::Statement that provides access to file-based storage mechanisms. Its quite possible to use things other than files as data souces, in which case we wouldnt use DBD::File, instead wed replace DBD::Files methods with our own. In the examples below, well use DBD::File, replacing only a few methods.

SQL::Statement provides SQL parsing and evaluation and DBD::File provides file-based storage. The only thing missing is a data source - what we actually want to store and query. As an example suppose we are going to create a subclass called Foo that will provide as a data source a simple file similar to a passwd file - one record per line, fields separated by colons, with only three fields "username, uid, gid".

Consider what needs to happen to perform a SELECT query on our Foo data:

* recieve a SQL string
* parse the SQL string into a request structure
* open the table(s) specified in the request
* define column names and postions for the table
* read rows from the table
* convert the rows from colon-separated format into perl arrays
* match the columns and rows against the requested selection criteria
* return requested rows and columns to the user

To perform operations like INSERT and DELETE, we also need to:

* convert rows from perl arrays into colon-separated format
* write rows
* delete rows

SQL::Statement takes care of all of the SQL parsing and evaluation. DBD::File takes care of file opening, reading, writing, and deleting. So the only things Foo is really responsible for are:

* define column names and postions for the table
* convert rows from colon-separated format into perl arrays
* convert rows from perl arrays into colon-separated format

In SQL::Statement subclasses these responsibilities are assigned to two objects, a ::Statement object is responsible for opening the table, defining the column names and positions, and for creating new ::Table objects. A ::Table object is responsible for reading, converting, writing, and deleting data.

Databrid is a browsing, retrieval and manipulation tool designed for the novice to the expert user. Databrid works on MySql and Oracle Database (versions 8 and above although not all functionality in the Browser is available for the lower versions). The core functionality of Databrid revolves around the tabbed areas within the Databrid application. The four main tabs in the main screen of Databrid are: SQL Editor, Browser, File and Jobs.

## SQL EDITOR ##
The SQL Editor tab allows you to write and run SQL and PLSQL. The tab provides the ability to use one of more sql autocompletion, word and syntax highlighting editors with automatic case adjustment for keywords. Provided with each editor is a table for displaying SQL query results and a text output area to display DBMS_Output output. Jobs can be run in the background allowing for the execution of multiple statements at any given time.

## BROWSER ##
The Browser tab allows the you to browse various parts of the database schema. The browsing is done via a particular schema user and displays information on tables, views, sequences etc. Features include the generation of database creation statements for tables, views etc, browsing table or view data, truncating tables, etc.

## FILE ##
The File tab allows you work with a CSV (comma delimited text file) and the database without having to load the CSV into the database. This tab has two areas that functionality: CSV Update and Database Update. CSV Update allows you to add additional columns to a CSV using a Select statement, including binding CSV column values to the Select statement. Database Update allows you to update the database using insert, updates, deletes or PLSql by binding the CSV column values into your statement.

## JOBS ##
This tab allows you to view which jobs are currently running or have finished. Jobs that are running can also be stopped.

StelsDBF is a DBF JDBC type 4 driver that allows to perform SQL queries and other JDBC operations on DBF files (dBase III/ IV/ V, xBase, FoxPro, FoxBase, Clipper).
StelsDBF driver is completely platform-independent and does not require installing additional client or server software to provide access to DBF files. It can be effectively used to create, process and export DBF databases in your Java applications.
Main features:
- It supports most keywords of ANSI SQL92
- It supports inner and outer table joins
- It supports CREATE, INSERT, UPDATE and DELETE statements
- It supports transactions
- It supports aggregate, converting, string and user-defined SQL functions
- It is a platform independent

PowerDNS Oracle Backend provides a backend which allows PowerDNS to use Oracle as its data store.

PowerDNS Oracle Backend is a backend driver for the PowerDNS nameserver which allows DNS data to be stored in an Oracle database. PowerDNS can load backend modules at runtime. This backend is fully configurable, and SQL statements can be specified in the configuration file.

FrameMaker::MifTree is a MIF Parser Perl module.

SYNOPSIS

use FrameMaker::MifTree;
my $mif = FrameMaker::MifTree->new;
$mif->parse_miffile(filename.mif);
@strings = $mif->daughters_by_name(String, recurse => 1);
print $strings[0]->string;
$strings[3]->string(Just another new string.);
$mif->dump_miffile(newmif.mif);

The FrameMaker::MifTree class is implemented as a Tree::DAG_Node subclass, and thus inherits all the methods of that class. Two methods are overridden. Please read Tree::DAG_Node to see what other methods are available.
MIF (Maker Interchange Format) is an Adobe FrameMaker file format in ASCII, consisting of statements that create an easily parsed, readable text file of all the text, graphics, formatting, and layout constructs that FrameMaker understands. Because MIF is an alternative representation of a FrameMaker document, it allows FrameMaker and other applications to exchange information while preserving graphics, document content, and format.

This document does not tell you what the syntax of a MIF file is, nor does it document the meaning of the MIF statements. For this, please read (and re-read) the MIF_Reference.pdf, provided by Adobe.

MifTree not only knows the MIF syntax, but it also has some understanding of the allowed structures (within their contexts) and attribute types. The file FrameMaker/MifTree/MifTreeTags holds all the valid MIF statements and the attribute type for every statement. This file may need some improvement, as it is created by analyzing a large collection of MIF files written by FrameMaker (and an automatic analysis of the MIF Reference, which showed several typos and inconsistencies in that manual). The current file is for MIF version 7.00.

Mergeant is a database administration tool.

Mergeant allows to connect to any database through the Libgda library (MySQL, PostgeSQL, Oracle, etc) and manage data within the database.

Any DML (data manipulation: insertion, update, deletion and selection) query can be created to help managing the data (queries can have optionnal parameters), from SQL statements or from a GUI interface.

The database structure (tables, data types, etc) can be browsed (modification is on the TODO list), and graphical representations of the database relations can be created.

SimpleDBM projects goal is to build a Relational Database Manager in Java. The planned features include support for:

Transactions
Write Ahead Log
Multiple Isolation Levels
BTree Indexes
Entry Level SQL-92
System Catalogs

A distinguishing feature of the project is that the DBMS is being built in a modular fashion. The aim is ensure that each module is usable on its own ; for example, the Lock Manager or the Log Manager modules can be used on their own even if the rest of the system is not of interest.

There will be two major sub-systems in the dbms backend. The Data Manager subsystem is named RSS, and is responsible for implementing transactions, locking, tuple management, and index management. This sub-system is currently under development.

The second major sub-system will be called SQL Manager. Its job will be to parse SQL statements, produce optimum execution plans, and execute the SQL statements. Development of this sub-system is expected to start sometime in 2006.

SimpleDBM is being built in Java 5.0 and will use new features such as java.util.concurrent package and Generics available in this version of Java. SimpleDBM will not be compatible with previous versions of Java.