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    Rapidant is a parallel-TCP-based, S/W High-Speed data transfer platform. It's purpose is to transfer massive data rapidly by consuming as much available bandwidth as possible. And this project provides an implementation of the Rapidant protocol using java. Developers Blog : http://www.facebook.com/rapidant Key Features * Fast data transfer based on parallel TCP * Efficient data transfer using real-time compression of data * Server-client architecture, in which the server supports multiple clients * Available either as an independent application or as a library for other application * Pure java implementation for working on various platforms
    13 years ago by @gresch
     
      bandwidthdatafiletransferframeworkshighspeedjavaprotocolsoftwaretcpip
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      Hazelcast is an open source clustering and highly scalable data distribution platform for Java, which is: * Lightening-fast; thousands of operations/sec. * Fail-safe; no losing data after crashes. * Dynamically scales as new servers added. * Super-easy to use; include a single jar. Hazelcast is pure Java. JVMs that are running Hazelcast will dynamically cluster. Although by default Hazelcast will use multicast for discovery, it can also be configured to only use TCP/IP for environments where multicast is not available or preferred.
      14 years ago by @gresch
       
        clusterclusteringdatadevelopmentframeworkjavamessagingmuticastsoftwaretcpip
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        Katta is a scalable, failure tolerant, distributed, data storage for real time access. Katta serves large, replicated, indices as shards to serve high loads and very large data sets. These indices can be of different type. Currently implementations are available for Lucene and Hadoop mapfiles. * Makes serving large or high load indices easy * Serves very large Lucene or Hadoop Mapfile indices as index shards on many servers * Replicate shards on different servers for performance and fault-tolerance * Supports pluggable network topologies * Master fail-over * Fast, lightweight, easy to integrate * Plays well with Hadoop clusters * Apache Version 2 License
        15 years ago by @gresch
         
          clouddataframeworkhadoopindicesjavalucenemapreducesearchsearchenginesearchingshardssoftwaretools
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          Teiid is a data virtualization system that allows applications to use data from multiple, heterogenous data stores. Teiid is comprised of tools, components and services for creating and executing bi-directional data services. Through abstraction and federation, data is accessed and integrated in real-time across distributed data sources without copying or otherwise moving data from its system of record.
          15 years ago by @gresch
           
            clusterdatadevelopjavajdbcjeeservicessoftwarevisualisationwebservices
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            A meta-programming approach to general data modeling. Introduction Meta-JB is a MetaClass/MetaObject layer providing generic access to model implementations, decoupling application logic from underlying implementation details, and allowing user interfaces (Swing, HTML, etc.) to be dynamically generated at runtime. By wrapping model implementations in MetaObject adapters, applications can interact with the model layer in a homogenous way. Description Meta-JB extends the Java Beans-based meta-programming concept to provide more generic access to object attributes and descriptions for any model object with an appropriate adapter. The descriptions of a class's properties (the MetaClass) and access to an object's attributes are decoupled from actual implementations by adapters implementing a Map-like name/value interface (the MetaObject). Because the thin framework is built on generic interfaces, it is not tied directly to real Java bean implementations and can also be used for anything that can access values by name. (Some examples are SQL result sets, HTTP request data, or simple hash maps.) Once a "class" has been described, the information can even be applied to different underlying implementations. The MetaClass/MetaObject layer is a foundation for dynamically generating user-level access to application object models. Toolkits are provided for generating Swing GUIs at runtime or dynamically rendering objects as XML using the class descriptions. On the drawing board is support for generating HTML forms and views as well. Future development may also extend to a collaborative data access layer.
            16 years ago by @gresch
             
              datadevelopframeworkjavajava_semanipulationmetamodelingreflectionsoftware
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              This document describes the implementation of a DAQ model. It provides a number of tools to develop a data acquisition system. To facilitate comunication between different objects, DAQ++ implements a very simple Observer model, in which some of the DAQ++ objects are defined as DAQpp::Observables and some as DAQpp::Observers. Observers subscribe to the messages defined in the Observables and are notified whenever a change occurs. The basis of the system is the DAQpp::Module object. It represents a detector or DAQ unit. As such, it implements the basic DAQ commands to get ready, start or stop the DAQ, retreive the data, etc.
              16 years ago by @gresch
               
                aquisitioncdatadataminingdevelopframeworkssoftwaretools
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                In order to solve web application vulnerabilities we have created HDIV (HTTP Data Integrity Validator) open source project. We can briefly define HDIV as a Java Web Application Security Framework. HDIV extends web applications’ behaviour by adding Security functionalities, maintaining the API and the framework specification. This implies that we can use HDIV in applications developed in Struts 1.x, Struts 2.x, Spring MVC and JSTL in a transparent way to the programmer and without adding any complexity to the application development. It is possible to use HDIV in applications that don’t use Struts 1.x, Struts 2.x, Spring MVC or JSTL, but in this case it is necessary to modify the application (JSP pages). The security functionalities added to the web applications are these: INTEGRITY: HDIV guarantees integrity (no data modification) of all the data generated by the server which should not be modified by the client (links, hidden fields, combo values, radio buttons, destiny pages, etc.). Thanks to this property HDIV helps to eliminate most of the vulnerabilities based on the parameter tampering. EDITABLE DATA VALIDATION: HDIV eliminates to a large extent the risk originated by attacks of type Cross-site scripting (XSS) and SQL Injection using generic validations of the editable data (text and textarea). CONFIDENTIALITY: HDIV guarantees the confidentiality of the non editable data as well. Usually lots of the data sent to the client has key information for the attackers such as database registry identifiers, column or table names, web directories, etc. All these values are hidden by HDIV to avoid a malicious use of them. For example a link of this type, http://www.host.com?data1=12&data2=24 is replaced by http://www.host.com?data1=0&data2=1, guaranteeing confidentiality of the values representing database identifiers. Also it is possible to hide the name of the parameters becoming the link into http://www.host.com?0=0&1=1. ANTI-CROSS SITE REQUEST FORGERY (CSRF) TOKEN: Random string called a token is placed in each form and link of the HTML response, ensuring that this value will be submitted with the next request. This random string provides protection because not only does the compromised site need to know the URL of the target site and a valid request format for the target site, it also must know the random string which changes for each visited page.
                16 years ago by @gresch
                 
                  datadevelophttpintegritysecuritysoftwarespringframework
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                  Talend has the most open and powerful data management solutions available as a packaged, out-of-box, ready-to-install platform. Talend's fundamental technology breaks with the market's leading proprietary solutions, associated with the open source model, significantly modifying the rules of the game in the data integration market.
                  18 years ago by @gresch
                   
                    computingtoolsdevelopetldbdataprogrammingsql
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