Good explanation! It would be awesome to have an end to end example using common technologies to apply this pattern such as AXON, Kafka Streams, Cassandra, etc..
Thanks for the tutorial. The trade api and eod trade are using same db for read and write purpose. The idea of cars defeated itself if we have this scenario bcz read and write simultaneously can choke the performance. There should be 2 separate db one for read and one fir write connected with kafka so that when write took place same data must be synchronized in read db as well
I see a flaw in the architecture. There is Dual write problem in matching service. The whole aim of cqrs is to eliminate distributed transactions and construct read model using events and commands.
Hi. Really good video, great explanation of the different components. Do you think we should be using RDMS for the all the tables or No-SQL like Cassandra?
CQRS is eventually consistent, so wouldn't that be a problem in this case study? E.g. You modify a stock price based on how many people buy into said stock, though if that stock isn't up to date then you will have people buying more expensive or cheaper stock than the realtime price, which then affects the data integrity.
Like i mentioned i have not considered all scenarios. The price updates gets pushed via something similar to response-processor (may be a socket connectivity) Also this is how the stock market works. Price changes every second/ms. We cannot compare it will ecommerce or other platforms where price doesn't change that frequently.
🔥🔥That is nicely done! You just solved in 18 minutes, what I was trying to accomplish in 4 four months. Keep up the good work! Subscribing now! Can you share the ppt?
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Good explanation! It would be awesome to have an end to end example using common technologies to apply this pattern such as AXON, Kafka Streams, Cassandra, etc..
Sure Javier. I have added it to the backlog
awesome as always... good thing is you have covered the challenges also.. otherwise everything looks pretty straight forward
Thanks for the tutorial. The trade api and eod trade are using same db for read and write purpose. The idea of cars defeated itself if we have this scenario bcz read and write simultaneously can choke the performance. There should be 2 separate db one for read and one fir write connected with kafka so that when write took place same data must be synchronized in read db as well
Its awesome explanation. Can you please share implementation part also if possible
Thanks for such amazing explanation.
I see a flaw in the architecture. There is Dual write problem in matching service. The whole aim of cqrs is to eliminate distributed transactions and construct read model using events and commands.
Thanks Hemanth. Would be happy to see the modified version so that i can share that with the audience
what are the other alternatives of CQRS for building microservices ?
Awesome ! highly appreciable. can u plz do a video how CQRS works with Apache Kafka in practical.
Sure bud. But will take sometime
Good information, thank you!!
Great video Ajay …. Could you please share the software you used to create the Architecture diagram please
It's google slides
Very well explained. Good job. Will you be able to make a hands-on video on this case study
Not immediately, but will do in the future
Hi. Really good video, great explanation of the different components. Do you think we should be using RDMS for the all the tables or No-SQL like Cassandra?
Nice explanation on CQRS and EventSource, Please can you explain what is SAGA and AXON.
Check the SAGA video. It's already there in the channel
Nice one .. Thanks
Super Awesome 👌
Very nice info, thanks a lot. Could you please create a video to implement this whole architecture. It will help us a lot.
Nice one Ajay :-)
I guess zerodha tech website will give more details about brokerage infra and architecture.. Heaps might be best for order book..
please explain with an example implementation
Nice video, please create a video on graph ql using aws graph ql service
Its there in the channel Bharath. It's called AWS AppSync
CQRS is eventually consistent, so wouldn't that be a problem in this case study? E.g. You modify a stock price based on how many people buy into said stock, though if that stock isn't up to date then you will have people buying more expensive or cheaper stock than the realtime price, which then affects the data integrity.
Like i mentioned i have not considered all scenarios. The price updates gets pushed via something similar to response-processor (may be a socket connectivity) Also this is how the stock market works. Price changes every second/ms. We cannot compare it will ecommerce or other platforms where price doesn't change that frequently.
Good content, easy to understan , thanks
🔥🔥That is nicely done! You just solved in 18 minutes, what I was trying to accomplish in 4 four months. Keep up the good work! Subscribing now! Can you share the ppt?
Is it a ppt?
Google slides
Can you share the slide please?
Make a video on it