The title here is being overlooked, its not _terrible_, its _hard_. Also this quote from the article:
> The bulk of these probably fall under "he obviously didn't understand X," or "you should never do Y!" in which case you would be absolutely right. The point of this is that I didn't understand the drawbacks or pain points until I'd gotten past the "toy" stage.
Most of what they discussed was indeed not great, but that was due to lack of understanding. I don't think anyone who does or promotes ES says it's _easy_. However, I would argue it _conceptually_ simple to understand (herein lies the fallacy people make simple != easy).
Like any pattern or tech that you are new too, it's going to be hard to build and operate in production (beyond the toy). Everyone takes for granted the decades we've had great tooling and operational patterns for state-oriented databases (mostly RDBMS').
And to be clear, event sourcing is "persistence strategy". What is mostly shown/discussed in the article is "event streaming" along with CQRS. They concepts are largely conflated. Once you understand, you won't be bamboozled.
Not to throw Confluent under the bus, but they have unfortunately written or promoted many articles for "event sourcing" use cases and this has confused everyone. You _can't_ do event sourcing with Kafka. It doesn't support optimistic concurrency control at the key level (where as something like EventStoreDB does natively or even NATS now with JetStream). Kafka if fantastic for what it is designed to do.. event streaming.
I've never heard of the term Event Sourcing. I AM familiar with Event Streaming. Some of what this article talks about surprised me - and I think it is because I don't fully understand the difference between Event Sourcing and Event Streaming.
I have not watched that clip, but as I said above, Confluent isn't a good resource for defining this term since Kafka cannot be used to do ES. I would suggest an article like: https://domaincentric.net/blog/eventstoredb-vs-kafka
that first article finds only one issue with Kafka-for-ES: limited number of partitions. Use pulsar, problem solved? Doesn't have the support or ecosystem of Kafka, but surely more than eventstoreDB.
There's two main reasons why Kafka as of today isn't a good fit for implementing event sourcing:
- Lacking support for key-based look-ups: when trying to materialize the current state of an entity, you cannot query Kafka efficiently for just those events (a partition-per-entity strategy doesn't scale due to the partion number limitation, which may change with KRaft in the future)
- Lacking support for (optimistic) locking: you cannot make sure to reject events based on outdated state, unless you apply work-arounds like a single writer architecture
They aren't solving the same problem. An event sourced entity (should) have a very small scope. It acts as a consistency boundary around some bit of state. Each event in "the stream" for that entity represents a state change. This is analogous to a database row which represents the _current_ state of the entity being modeled for that table.
Like a table, there can be an arbitrary number of rows (>millions), thus you could have millions of event streams. You can't have millions of Kafka partitions. The scope/scale of a Kafka partition is not designed for that small granularity.
Again, I have no issue with Kafka and I think Pulsar is superior in the event streaming/platform space. I also the Kafka ecosystem is impressive and I love listening Confluent Cloud podcast! But it is not designed for this use case.
> The bulk of these probably fall under "he obviously didn't understand X," or "you should never do Y!" in which case you would be absolutely right. The point of this is that I didn't understand the drawbacks or pain points until I'd gotten past the "toy" stage.
Most of what they discussed was indeed not great, but that was due to lack of understanding. I don't think anyone who does or promotes ES says it's _easy_. However, I would argue it _conceptually_ simple to understand (herein lies the fallacy people make simple != easy).
Like any pattern or tech that you are new too, it's going to be hard to build and operate in production (beyond the toy). Everyone takes for granted the decades we've had great tooling and operational patterns for state-oriented databases (mostly RDBMS').
And to be clear, event sourcing is "persistence strategy". What is mostly shown/discussed in the article is "event streaming" along with CQRS. They concepts are largely conflated. Once you understand, you won't be bamboozled.
Not to throw Confluent under the bus, but they have unfortunately written or promoted many articles for "event sourcing" use cases and this has confused everyone. You _can't_ do event sourcing with Kafka. It doesn't support optimistic concurrency control at the key level (where as something like EventStoreDB does natively or even NATS now with JetStream). Kafka if fantastic for what it is designed to do.. event streaming.