ceencee

4 ms·

1. 1.▲
   by ceencee 3y ago

   I feel like this is frankly uninformed. Many iceberg shops seem to rely heavily on Spark as a primary engine. And databricks has a history of being a hostile oss force with the culture of the spark project being toxic from the start and del
2. 2.▲
   by ceencee 3y ago

   Kafka can sustain sub 20ms at millions or even billions per second scale. Processing time delays is bad consumer code and partition design smell. Aka , your consumer shouldnt depend on a slower resource within an ordering domain. This can a
3. 3.▲
   by ceencee 3y ago

   This is a ridiculous statement if you really build an EDA. Kafka is what enables the decoupling.
4. 4.▲
   by ceencee 3y ago

   Pretty much every bank uses kafka ad the central messaging layer. What people are missing in almost every post here is the write once read many without data duplication and with different offsets is the killer app for Kafka beyond just the
5. 5.▲
   by ceencee 3y ago

   Who is running single az deployments who also cares about data loss and availability? Seriously? I’ve personally supported 1000s of kafka deploys and this isn’t a thing in the cloud at least. There is no call for wanting fsync per message,
6. 6.▲
   by ceencee 5y ago

   I see posts like this a lot, and it makes me wonder what the heck you were using Kafka for that Postgres could handle, yet you had dozens of clusters? I question if you actually ever used Kafka or just operated it? Sure anyone can follow th