1. Stream-Table Duality beginner

    A service keeps an in-memory map of product prices built by consuming a compacted topic, instead of calling the pricing service on each request. A colleague asks why the map is not just a cache. What is the honest answer, and what does the service now own?

    2 min answer materialized viewcompactioncacheconsistency
  2. Stream-Table Duality beginner

    A team is told that a table and a stream are two views of the same thing. They have a Postgres table holding 12 million account balances and are asked to produce the stream of changes that produced it. Why does the equivalence only run one way in practice, and what has to exist before it runs the other way?

    3 min answer changelogcompactioncdcoutbox
  3. Stream-Table Duality intermediate

    Review this design. Each of 18 services embeds a Kafka Streams GlobalKTable of a 9-million-row customer topic so that lookups are local, each instance holding it in RocksDB on local disk. Instances take 11 minutes to become ready. What would you remove, what would you change, and what would you leave alone even though it looks odd?

    3 min answer globalktablematerialised viewrestore timedeploys
  4. Stream-Table Duality advanced

    Vitess - the MySQL sharding layer built at YouTube and later a CNCF project - reshards a live keyspace by having each target shard build its tables with a copy phase and then follow the source's binlog from the position where the copy ended. The same stream is exposed to applications as VStream. What does that design buy and where would copying it be a mistake?

    3 min answer youtubevitessvreplicationresharding
  5. Stream-Table Duality advanced

    What does stream-table duality mean practically, and how does it change system design?

    2 min answer stream-tablechangelogmaterialisationcdc