Notion replaced slow warehouse syncs with a CDC pipeline (Debezium to Kafka to Hudi on S3) processed with Spark.
OpenAI's Habitat storage platform went from one shared Azure Cosmos DB container, to dedicated single-tenant containers that pushed capacity planning onto every product team, and back to a shared container by default once Azure added hot-key throttling, request-priority QoS and a new serverless mode where each physical partition scales to 10K RU/s and splits on RU usage. After failover and failback outages in late 2024, OpenAI and Azure now co-own testing and monitoring. Replicating small latency-critical datasets widely, a Valkey lookaside cache invalidated through the Cosmos DB change feed, and a Rust rewrite of the proxy cut global read p50 from about 120 ms to about 10 ms.
Netflix moved older data in its multi-petabyte TimeSeries Abstraction out of hot Cassandra storage in two steps. First, Kafka and Flink streamed events to S3 as Parquet files, which a daily job compacted into small, time-sorted row groups with Bloom filters cached in EVCache (p50 ~150 ms, p99 ~500 ms). The second design skips that streaming pipeline: a ReadOnlyCompactionStrategy aligns immutable SSTables to token ranges, and a custom pluggable Memtable (Cassandra 4.1) reads directly from existing Cassandra backups in S3. It now holds over 15 PB of compressed cold data, cut disk usage on affected clusters from 80% to 7%, and improved p90 latency by ~30%.
OpenAI's Habitat storage platform grew from a Python client library over Cosmos DB into a central service handling 70M+ requests per second. The team ran many low-concurrency Python processes to keep asyncio delay down, switched aiohttp connection reuse from LIFO to FIFO to stop a metastable failure, used Envoy for connection fan-in, kept a deliberately simple NoSQL API, then rewrote the service in Rust.
GitHub broke one huge push-processing job into smaller, independently retried jobs driven by Kafka events.