Application-Level Forward Erasure Correction (AL-FEC) codes are a key element of telecommunication systems. They are used to recover from packet losses during large scale content distribution, for instance within the FLUTE/ALC (file transfers) and FECFRAME (continuous real-time media transfers) protocols of the 3GPP Multimedia Broadcast and Multicast Services (MBMS) standard. However currently standardized and deployed AL-FEC codes for these protocols (e.g., Raptor(Q) or LDPC-Staircase) are all block codes which means that the data flow must be segmented into blocks of predefined size. Surprisingly AL-FEC codes based on a sliding encoding window have not yet been considered in spite of their major advantages. This work analyzes both types of codes in the context of real-time (e.g., multimedia) flows. More precisely, it details how to initialize block and convolutional AL-FEC codes to comply with real-time constraints and introduces the " decoding beyond maximum latency " optimization to convolutional codes. Then it compares the added FEC-related latency of both solutions and the decoding throughput of the two codecs. This work highlights the major benefits of convolutional codes for the large scale distribution of real-time flows and supports the idea of extending FECFRAME specifications (RFC 6363) to support convolutional FEC codes.