Open Source Big Data Tools

The article explains the design and the characteristics of a new open source content aggregation system. Among the features of the program, stands out a new processing engine of syndication channels, monitoring capability of information recovery in real time, the possibilities of the configuration of aggregator behavior, automatic classification of contents and new models for representation of information from relational interactive maps. On the other hand, the aggregation program, which named AXYZ, is designed to manage thousands of syndication channels of RSS format. Furthermore it also provides statistics that can be used to study the production of any producer subject and the impact of the information that published in other sources. The result that has been obtained in the research, allow to create modules capable of compare the relationship between different news or information from different sources, their degree of influence and their detection by the patterns.

Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability. Messaging patterns including publish/subscribe, request/reply and streaming. Financial grade transactional message. Built-in fault tolerance and high availability configuration options base on DLedger. A variety of cross language clients, such as Java, C/C++, Python, Go. Pluggable transport protocols, such as TCP, SSL, AIO. Built-in message tracing capability, also support opentracing. Versatile big-data and streaming ecosytem integration. Message retroactivity by time or offset. Reliable FIFO and strict ordered messaging in the same queue. Efficient pull and push consumption model. Million-level message accumulation capacity in a single queue. Multiple messaging protocols like JMS and OpenMessaging. Flexible distributed scale-out deployment architecture. Lightning-fast batch message exchange system.

Cube Platform is a decentralized grid computing system that uses P2P Pastry protocol for communication between nodes. It's a big data storage written in Java.

Source code for be able to use Relation Tags. It is part of project VocabularyMem but can be used separately. Relation Tags are tags which can be relationed together . For example tag "Paris" and tag "France" can be relationed with a relation "is part of". This code is created from 0 and is able to define which type of relation we use, using most elemental mathematic properties. It is strongly recommended to read "Relation Tags guide for programmers". Inside source zip, also contains dialogs for set properties of this extended tags. All this dialogs files finish either with "...dlg.cpp" or ",,,dlg.h". Please read "readme" file. It is recommended to use a binary matrix class like BinMatrix in order to have enough speed for calculations of implicit relations in a system of bogus tags with big data. Need to be compiled with C++11 and Qt libraries