Whereas traditional Desktop Grids rely on centralized servers for data management, some recent progress has been made to enable distributed, large input data, using to peer-to-peer (P2P) protocols and Content Distribution Networks (CDN). We make a step further and propose a generic, yet efficient data storage which enables the use of Desktop Grids for applications with high output data requirements, where the access grain and the access patterns may be random. Our solution builds on a blob management service enabling a large number of concurrent clients to efficiently read/write and append huge data that are fragmented and distributed at a large scale. Scalability under heavy concurrency is achieved thanks to an original metadata scheme using a distributed segment tree built on top of a Distributed Hash Table (DHT). The proposed approach has been implemented and its benefits have successfully been demonstrated within our BlobSeer prototype on the Grid’5000 testbed.