Storage, warehouses, pipelines, and analytical systems.
OpenAI kept one PostgreSQL primary alive for a massive read-heavy workload by moving reads to replicas, pooling connections, protecting caches, rate limiting spikes, and pushing write-heavy workloads elsewhere. The useful lesson is not "Postgres scales forever." It is knowing which pressure you are actually under.
Flink is not just a library that runs a loop over events. It turns a streaming program into a distributed dataflow, splits operators into parallel subtasks, places those subtasks into task slots, and keeps state recoverable with checkpoints.
Resolution is only the pixel count. The picture also needs enough bits to describe those pixels. A 4K stream can have more pixels than a theater image and still give each pixel far less data.
Redis, Flink, databases, and Bloom filters can all remove duplicates, but they are not interchangeable. The right choice depends on where the duplicate appears, how long you must remember it, and what happens if you are wrong.
Before KRaft, Kafka used ZooKeeper as its coordination layer: broker membership, controller election, topic metadata, partition leaders, and ISR state all needed a consistent place to live.
Analytical databases like BigQuery and Redshift are fast because they stop pretending every query needs every field. They read columns, compress patterns, and skip the bytes your question never asked for.