Hadoop offers robust data recovery capabilities, with HDFS ensuring data replication across nodes for fault tolerance. If a task fails, Hadoop re-executes it on another node. Spark uses Resilient Distributed Datasets (RDDs) that automatically recover from node failures, but its in-memory nature can pose risks if a node fails and data is not replicated elsewhere​.