Free ado net data access software for linux

Firebird .NET Data Provider is an ADO.NET data provider for Firebird. Firebird .NET Data Provider is written in C# and provides a high-performance native implementation of the Firebird API. It also includes an implementation of the Firebird Services API and Firebird array datatype support.

Firebird is a relational database offering many ANSI SQL standard features that runs on Linux, Windows, and a variety of Unix platforms. Firebird offers excellent concurrency, high performance, and powerful language support for stored procedures and triggers. It has been used in production systems, under a variety of names since 1981.

Firebird is a commercially independent project of C and C++ programmers, technical advisors and supporters developing and enhancing a multi-platform relational database management system based on the source code released by Inprise Corp (now known as Borland Software Corp) on 25 July, 2000 under the InterBase Public License v.1.0

Sowa Data Capacitor is a unified Java API for accessing data in several different forms, such as XML, database or memory.

Installation:

Sowa Data Capacitor now not need any dependences (except ant), but itll propably have.

To build it you have to have:

* Apache Ant
* JDK of Java 2

To use it you have to have:

* JVM of Java 2

To build it just run build in base catalogue.

Version Convention

First noumber(maior) is api version, except 0 and 1 which is maturity change.
Itll change only if api is completly rewritten.

Second(minor) means small api(especcially adds) changes, which could break(but
not have to) plugins but not applications.

Third(patch) means some improvement, which not change api.

Dev means version for developer(of plugins optionally applications), Alpha
and Beta test release.

Last noumber mark order of releases.

Netacct-mysql is modified version of traffic accounting daemon net-acct which stores collected data in MySQL. It supports writing accounting information in a single line in MySQL per day for every IP (mrta style).
Netacct functions by analogy with sniffer, i.e. it keeps track of all the traffic passing through the network interfaces assigned by the configuration file. Data are stored in the memory and periodically saved in the database. The default data save period is 300 seconds (see option "flush" in the config file).
The application is used for accounting of the network traffic passed through your router/gateway. It is based on the libpcap library and functions as a userspace daemon. Options for dividing the network traffic into 4 categories:
- international
- peering
- direct
- local
The traffic accounts are saved in a database, and for the time being MySQL and Oracle are supported. As libpcap is used for gathering the network data the application runs (for the moment) on the following operating systems:
- Linux
- FreeBSD
- OpenBSD
- Solaris
For more detailed information regarding a particular OS, please read the FAQ file.
Enhancements:
- netacct.h:
- process.c:
- naccttab.sample:
- fixed disable fields in config file, now it works does not write some fields in dump file - fixed

GData Java Client provides a library and source code that make it easy to access data through Google Data APIs.

The Google data APIs ("GData" for short) provide a simple standard protocol for reading and writing data on the web. GData combines common XML-based syndication formats (Atom and RSS) with a feed-publishing system based on the Atom publishing protocol, plus some extensions for handling queries.

Google also provides a set of client libraries for interacting with GData-enabled services, in a variety of programming languages. Using these libraries, you can construct GData requests, send them to a service, and receive responses.

Xephyrus Data Structures Tag Library provides an easy way to create and manipulate the contents of common Java data-structures such as maps and lists.
Enhancements:
- The library was polished up.
- Several improvements were made and a few bugs were fixed.
- This version is aimed at Java 5 and JSP 2.0.

Dataxi project is a collection of tools for developing form-based information systems. Dataxi enables one to quickly build an application based on forms with which the user can access the underlying database in order to query, read, edit and write. Dataxi is the link between the user interface and the database.
Dataxi is an OS and enviroment independent product. It follows HTML and SQL standards to such extend that interoperability with all browsers and database backends should be supported.
Dataxi runs on all major operating systems as is or only with minor changes in ini -files.
The purpose of Dataxi is to take the pain away from the most boring phase in the data access application development: user interface designing and programming. Ones you have defined the layout of the form and location for columns, you are done, unless you prefer setting data validation and output format features and other niceties.
A database is a structured collection of data. It may be anything from a simple shopping list to a picture gallery or the vast amounts of information in a corporate network. To add, access, and process data stored in a computer database, you need a database management system such as MySQL. Since computers are very good at handling large amounts of data, database management plays a central role in computing, as stand-alone utilities, or as parts of other applications.
Enhancements:
- This version works with both PHP 4 and 5.

Data::Locations - magic insertion points in your data
Did you already encounter the problem that you had to produce some data in a particular order, but that some piece of the data was still unavailable at the point in the sequence where it belonged and where it should have been produced?
Did you also have to resort to cumbersome and tedious measures such as storing the first and the last part of your data separately, then producing the missing middle part, and finally putting it all together?
In this simple case, involving only one deferred insertion, you might still put up with this solution.
But if there is more than one deferred insertion, requiring the handling of many fragments of data, you will probably get annoyed and frustrated.
You might even have to struggle with limitations of the file system of your operating system, or handling so many files might considerably slow down your application due to excessive file input/output.
And if you dont know exactly beforehand how many deferred insertions there will be (if this depends dynamically on the data being processed), and/or if the pieces of data you need to insert need additional (nested) insertions themselves, things will get really tricky, messy and troublesome.
In such a case you might wonder if there wasnt an elegant solution to this problem.
This is where the "Data::Locations" module comes in: It handles such insertion points automatically for you, no matter how many and how deeply nested, purely in memory, requiring no (inherently slower) file input/output operations.
(The underlying operating system will automatically take care if the amount of data becomes too large to be handled fully in memory, though, by swapping out unneeded parts.)
Moreover, it also allows you to insert the same fragment of data into SEVERAL different places.
This increases space efficiency because the same data is stored in memory only once, but used multiple times.
Potential infinite recursion loops are detected automatically and refused.
In order to better understand the underlying concept, think of "Data::Locations" as virtual files with almost random access: You can write data to them, you can say "reserve some space here which I will fill in later", and continue writing data.
And you can of course also read from these virtual files, at any time, in order to see the data that a given virtual file currently contains.
When you are finished filling in all the different parts of your virtual file, you can write out its contents in flattened form to a physical, real file this time, or process it otherwise (purely in memory, if you wish).
You can also think of "Data::Locations" as bubbles and bubbles inside of other bubbles. You can inflate these bubbles in any arbitrary order you like through a straw (i.e., the bubbles object reference).
Note that this module handles your data completely transparently, which means that you can use it equally well for text AND binary data.
You might also be interested in knowing that this module and its concept have already been heavily used in the automatic code generation of large software projects.
Enhancements:
- Fixed test file "02___refcount.t" to auto-adjust the offset dealing with self-ties not incrementing
- the refcount in some Perl versions.
- Added a warning to "Makefile.PL" that Perl versions including and between v5.6.1 and v5.7.0 are not fully supported (test file "11_______dump.t" dumps core).

DBD::ADO::Const is a Perl module for ADO Constants.

SYNOPSIS

use DBD::ADO::Const();

$ = "n";

my $Enums = DBD::ADO::Const->Enums;

for my $Enum ( sort keys %$Enums )
{
print $Enum;
for my $Const ( sort keys %{$Enums->{$Enum}} )
{
printf " %-35s 0x%Xn", $Const, $Enums->{$Enum}{$Const};
}
}

In the OLE type library, many constants are defined as members of enums. Its easy to lookup DBD::ADO constants by name, e.g.:

$ado_consts->{adChar} == 129

Unfortunately, Win32::OLE::Const does not preserve the namespace of the enums. Its a matter of taste, but I think

$ado_consts->{DataTypeEnum}{adChar} == 129

makes the code more self-documenting.

Furthermore, many DBD::ADO methods return numeric codes. Transforming these codes into human readable strings requires an inverse lookup by value. Building the reverse hash for e.g. all datatypes requires that datatype constants can be distinguished from other constants, i.e. we need the namespace preserved.

The Enums() method of this package return a hash of hashes for exactly this purpose.