1. A method for operating a big-data platform comprising: at a data analysis platform, receiving discrete client data; storing the client data in a network accessible distributed storage system that includes: storing the client data in a real-time storage system in a row format; merging the client data into a columnar-based distributed archive storage system; identifying a merge status for the client data merged into the archive storage system, wherein the merge status indicates a redundancy of client data between the real-time storage system and the archive storage system; receiving a data query through a query interface; and processing the data query by selectively interfacing with the client data from the real-time storage system and archive storage system, according to a data mapping and reduction process, wherein the real-time storage system and the archive storage system are different, wherein processing the data query comprises: (i) converting the single data query from a relational database-type query format to a first converted query format compatible with the real-time storage system, (ii) converting the single data query from the relational database-type query format to a second converted query format compatible with the archive storage system, (iii) cooperatively querying the real-time storage system and the archive storage system by distributing, in parallel, the first converted query over the real-time storage system and the second converted query over the archive storage system, (iv) using the merge status and timestamps of the client data in the real-time storage system and the archive storage system to skip client data from either the real-time storage system or the archive storage system if the skipped data is accounted for in the other of the real-time storage system or the archive storage system, and (v) retrieving a single cohesive query result that incorporates real-time data and archive data returned from the first converted query and the second converted query, respectively, wherein merging the client data into a columnar-based distributed archive storage system comprises storing the client data in the archive storage system in a columnar format, and wherein interfacing with the client data from the archive storage system comprises: converting, by using a query processing cluster, at least a portion of the data query to the mapping process and the reduction process; and executing the mapping process and the reduction process by using the query processing cluster.