Ceramic, a decentralized data network, faces scalability challenges despite its design for high throughput. Its stream-based architecture, where each data object maintains independent state, enables parallel processing but struggles with complex data integration across nodes. Sharding is not explicitly detailed, potentially leading to data model replication across nodes, which may strain resources as data volume grows. Latency issues arise from network communication, especially for applications requiring real-time queries. While Ceramic's event streaming protocol supports mutable streams and composable data, ensuring consistency without compromising performance remains a hurdle. Solutions like optimized node configurations and hybrid models could mitigate these issues, but further research is needed to balance decentralization, security, and scalability effectively.