Structured Streaming With Stateful Processing And Rocksdb State Store

Unified engine for large-scale data processing and ML.

Unique: Unifies batch and streaming APIs through the same DataFrame/SQL abstraction, with TransformWithState operator enabling arbitrary stateful transformations backed by RocksDB state store with automatic compaction and recovery through write-ahead logs

vs others: Simpler than Flink for SQL-based streaming because it reuses Catalyst optimizer; more reliable than Kafka Streams for exactly-once semantics because checkpoint-based recovery handles both state and output idempotency