Today, modern society relies heavily on electronic and telecomunications devices that are critically vulnerable to Space Weather effects. Space Weather events are originated in the Sun-Earth system and may have the ability to distort high frequency radio signals, satellite based communications, precision positioning based on satellite constellations, and in some latitudes, can affect power grid distribution systems and even human health in space. The knowledge of near Earth space conditions can trigger alert, precaution, recovery or even some mitigation actions over technology failure due to SW effects. Fields such as aeronautics, navy, mining and other industries use geodesic data based on precision positioning and depends on radio signal reliability. So that, a Space Weather monitoring system can benefit different socio-productive sectors that are affected by adverse Space Weather effects. Currently, there are numerous world wide databases about solar observations, solar wind, magnetic and atmospheric data. In Argentina and in Universidad Nacional de Tucumán (in the Observatorio Ionosférico Tucumán de Alta Atmósfera en Baja Latitud) in particular there are ionospheric monitoring instruments deployed to study the upper atmosphere. These instruments provide the system with raw data and in some cases with not structured data. All these data sources involve a great amount of data to process. Dataset management has special role in any monitoring system. Obtaining data systematically and with high reliability is a main issue, so is important to be able to acquire, store and process heterogenic data efficiently. Moreover, a monitoring system must been able to deliver a product according to clients necessity. Here, we propose the development of a Space Weather monitoring system with the quality to efficiently process multiple heterogenic data sources in an asynchronous manner