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WhiteBear is a client/server application database engine that provides functions for finding, creating, manipulating, storing and extracting data from databases. It supports a wide range of data formats such as CSV, TXT, HTML and XML. It is designed to work with any database server and can be embedded in a web application or linked to from a client. It supports API calls and can be used from Java, C/C++, Delphi or Visual Basic. WhiteBear includes a set of tools that can be used to access client-server, embedded or file-based databases. It supports CLI, ODBC, JDBC, OLE DB and JDO. NOTE: The current release is actually a preview of the product and not all promised functions are available in this beta version. Features: The following features are available: o Basic database and query access o Data export and import (CSV, TXT, HTML, XML) o Data tools for xml and html o Client server database access with JDBC, OLE DB and ODBC o File-based database access o CLI and GUI administration o Data validation o Data sorting o Raw data retrieval o Database optimisation o Multiple simultaneous database access (ODBC) o Graphical query display o Multi database support (ODBC, JDBC, OLE DB) o Foreign key support o Option to use Unix/Windows DLLs (OLE DB and ODBC) o MySQL, SQLite, PostgreSQL, Oracle and DB2 database support o LDAP database support o OpenOffice/MS Office and Access files import/export o XML database support You are here SQLite is an advanced SQL database engine designed for use in mobile, embedded, server-side, desktop and other applications. SQLite is designed to make SQL and relational database access fast, lightweight and portable. The source code is freely available for anyone to use under the GNU GPL. The library is provided for use with most any programming language. The use of SQLite is completely portable, regardless of the operating system or CPU being used. SQLite is being developed to provide a full featured SQL database engine that is: * Easy to use. * Stable. * Free. * Compact. * Portable. * Lightweight. * Allows high performance. A high performance SQL database engine does not require any features to be turned off to save on performance
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KeyMacro is a tool to process key/data strings in a white box environment. This tool is suitable for use with key-like data like passwords or other ID/data strings. It processes the data string in a stream mode. There are no limitations on the length of the data string. KEYMACRO aims to be fast and easy to use. It provides the following commands: “start” – This command starts a key macro. “stop” – This command stops a key macro. “process” – This command processes the data string and puts it in a stream mode. “split” – This command splits the input string into strings of equal length (width of the pipe symbol). “hash” – This command hashes the data string using a chosen hash algorithm. “print” – This command prints out the data string. KEYMACRO Syntax: The usage of this tool is very simple: – A data string is entered. – The “start” command is used. – The data string is processed by KeyMacro. – The “stop” command is used to stop the process. – The “print” command prints out the processed data string. – The “hash” command processes the data string using a chosen hash algorithm. This key macro tool is an easy to use tool and requires little or no programming. The output stream can be easily printed to a file or sent over a network, etc. If you encounter any problems or bugs, please notify us. KeyMacro is under GPL version 2.0 licence. For more information, please read the license document and visit the source code page. The AVRP(at)pss(dot)org mailing list has information on the latest news from PSS about its security products. This list is archived at To subscribe, send mail to avrp-subscribe@avrp.pss.org with a single empty line in the body. To unsubscribe, send mail to avrp-request@avrp.pss.org with “unsubscribe” in the subject of the message. as we’re constructing. 2edc1e01e8
WhiteBear
As a white label solution, WhiteBear can be integrated easily with various LOB/financial applications. This white label solution integrates into any ERP or CRM application (desktop or web) to provide a comprehensive solution for enterprise information management. WhiteBear provides a complete, reliable, scalable, and cost-effective database solution to meet your database needs. WhiteBear has been recognized as the leading Java-based NoSQL database for the financial industry. Financial transactions processing and big data analytics are our passion. Our financial transaction processing is guaranteed to have a minimum downtime and the highest availability. We develop optimized financial transaction processing engines to handle high transaction volume. By using our financial transaction engine, you will be able to process thousands of transactions per second. Our transaction processing engine is based on the Java language and the Hibernate framework. WhiteBear supports the handling of all Windows and UNIX platforms such as Windows, Linux, Mac, etc. WhiteBear supports the following data types: Unicode and Unicode character support Floating-point and integer data types Some data types can be up to 20 times faster than Java data types! Geo-positioning Algorithms for top-level selection Algorithms for B-tree index Streaming replication and snapshot support Hibernate and Spring support Flexible implementation of the database in an application server environment. Integration into any ERP or CRM application (desktop or web) to provide a comprehensive solution for enterprise information management. The white label product can be deployed on any supported J2EE platform. Data encapsulation, where the data structure can be reconstructed using just one or several parts. The most common example is a table with a primary key, foreign keys and other columns and rows. If you want to reconstruct this structure only using a part of the data, you will receive the corresponding fragment of the database. You can also encapsulate a table by one or several columns. If you select a single column and a table that contains it, you will receive the complete data structure. Clustering Clustering is based on the main idea that data is not uniformly distributed. When an application uses one or several tables to store information, the average usage is the same for all the tables. You may have some data that is significantly more often used than other data.
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