The key thing to mention is that If sensor metrics are spread across multiple partitions, they can still be read out of order, so in-order is only guaranteed within the partition.
Ah, this is amazing, I have soome junior developers that I am training on MS Architeture we are now at the integration point and wanted to see which is better from our case. It seems we might be using both options for us. Thanks
amazing topics, and video been thinking about learning more about rabbit mq and kafka for awhile. wanted to know the diff. this answers my question in mind.
Great! I should make the caveat though that you should definitely check the official docs of both technologies at this point, because it is very possible that they have evolved significantly!
Im building out a game with a microservice architecture and an eventbus system. I want to know some thoughts on the idea of using both kafka AND rabbitmq. I would use kafka for the user auth service where all user data will be saved to disk to maintain reliable syncing with other services at all costs. My thought is that the auth service is by far the most critical service and needs a robust system in place. I am ok with the processing time taking a bit longer as this is just for the signing up/registering a user process(this only happens one time per user). Then for all other game related events, it will be handled with rabbitmq to utilize the in memory speeds. I understand that setting up/maintaining these two systems will be more difficult, but overall do you think this idea has some merit to it?
Well, you may not love my answer, but considering this is a personal project, I think that you're building for scale that you don't need :) I'd probably just use some existing OAuth service and for the game related events you could always just have the server connect to all clients via websockets.
This was a really helpful overview of the messaging systems. Can you do a video that goes more into the implementation details of the message brokers you discussed? For instance, answer to questions like how and under what conditions does Kafka guarantee exactly once message delivery and what sort of guarantees these message brokers give in case of failures etc.
The brokers themselves don't really give any guarantees I'd say, but rather the broker in combination with a stream processing framework is where you start seeing those. Hopefully the stream processing video clears that one up a bit.
Wait I think RabbitMQ has some failover strategies? I think they also have quorum queues and classic queues where quorum queues actually have a persist log on disk? Not 100% sure about what I am saying though, maybe a bit too specific to RMQ. someone correct me if I am wrong.
You may be right - when I talk about these technologies I try to just focus on "in memory" versus "log based" because specific implementations can change all the time. It's very possible that depending on how you configure RMQ you can do any of those things.
Wanted to clarify the same thing. RMQ supports durable queues but just to be clear that means saving messages in the queue not yet ACK'd when the system goes down or memory is unavailable. Doesn't mean full replay.
RabbitMQ has a different storage options that are log-based. Calling it an "in memory" doesn't sound right. Not sure about others in a list but it could be the same case with them.
Yeah I always make this videos with the caveat that they could very well be incorrect. When a technology is open source, it can adapt significantly over time, and additionally people like to throw in a lot of features so that they have more to advertise for the product. A better title for the video would be "in memory vs. log based message brokers", but I just like to clickbait because I'm a narcissist.
Low latency backbone used by trading firms beat these two by wide margins. I guess these are designed for high throughput whereas LLBs are designed for low latency.
I guess u r talking about ultra low latency full stack systems which uses combination of HW and SW to get really low latencies. Solace is one of such vendor. These systems have very limited use cases and mostly they are for trading. Kafka and RabbitMQ are all about scale and provides good enough latencies sufficient for wide range of use cases.
Great videos + How someone so young can have so much knowledge .. but bro why do you have named it -> Systems Design Interview 0 to 1 ? Systems Design 0 to 1 could have been an apt name .. don't you think? its more useful than just for interviews..
I think it's harder to speak authoritatively about actually systems because there's a lot more "it depends" and existing company considerations going into making those choices :). Plus, these things change so fast that for the purposes of accuracy about the technologies my videos are good for interviews, but could be incorrect IRL
6:16 if its a message queue and last message processed by consumer B was M2 then according to Queue next message to process should be M1 but you are saying next message to be processed is M3. This is confusing explain / correct me if I'm wrong
I don’t see anything inherent in the log based queue that would limit throughput - except the slower reads from the disk. I feel like the semantics of the queue should be independent of the way it is stored - if that makes sense.
I was thinking about this more and I suppose the limits on memory could be one reason why the semantics are different. When you’re processing from memory you need to clear items out or the queue gets too big and you’ll get thrashing / crashing. I’ve seen this happen with RabbitMQ at work.
For a visual learner like me, I understand but the way you scribbled all over the board. It can throw people off. Just a bit of advice maybe you can take some goodness from. Great video though man!
In practice this may be true, I'd have to look at benchmarks. I think that from an interviewing perspective though, knowing the architectural differences between them and what that means (at least in theory) is important.
