⏱ Chapter Timestamps =================== 0:00 - Agenda 1:00 - What is Batch? 1:15 - What is Stream? 1:32 - What is Micro-Batching? 2:19 - When to use batch processing 3:47 - When to use stream processing 6:16 - Use-case: Analytics Application 10:52 - Case study: Netflix Kinesis Data Streams 11:43 - Case study: Nasdaq’s Architecture using Amazon EMR & Amazon S3 12:36 - Summary
Just wow!! Maybe you don't realize how helpful and resourceful is your video. I just got my certificate in data engineering but let me tell you this, you are so concise and clear in your explanations that I feel more confident now using stream processing. From time to time I will come back to you if I have any questions. I do have it but I will ask them later
Wish I came across this channel earlier , nonetheless better late than never . Superb content and numbers shout that this channel is pretty underrated .
Thanks for your efforts this is the next level of learning on batch and stream process my request could you please start a session on scala programming
Are you saying that Amazon Kinesis uses Apache Flink? As I understand, they have similar functionality, but Kinesis is proprietary while Flink is open source.
For realtime steam processing. If i send each frame into my ML Inference load balanced servers as a post request, even this works right? Then why do we need kafka
Hi Anderson, Amazon Kinesis Data Analytics is a serverless offering which runs on ApacheFlink behind the scenes. We can integrate it to other AWS services, however we cannot use spring streaming inside data analytics
Thanks for the video. Could you please state why do we need to place analytics service before AWS streams? What should this service do in this particular example?
this video is really helpful . can you please make video on concepts IBM MQ and avro kafka and Tibco etc . message queue and schema registration etc topics uses in scripting in performance testing and what are the goel to uses these concepts in scripting in performance testing with uses case examples to get proper visualization
⏱ Chapter Timestamps
===================
0:00 - Agenda
1:00 - What is Batch?
1:15 - What is Stream?
1:32 - What is Micro-Batching?
2:19 - When to use batch processing
3:47 - When to use stream processing
6:16 - Use-case: Analytics Application
10:52 - Case study: Netflix Kinesis Data Streams
11:43 - Case study: Nasdaq’s Architecture using Amazon EMR & Amazon S3
12:36 - Summary
Just wow!!
Maybe you don't realize how helpful and resourceful is your video.
I just got my certificate in data engineering but let me tell you this, you are so concise and clear in your explanations that I feel more confident now using stream processing.
From time to time I will come back to you if I have any questions. I do have it but I will ask them later
where did you get your certificate from bro?
It's hard to find quality content about advanced topics like this. Well explained 👍
Glad it was helpful!
This video was thorough, clear, and very helpful, thanks!! I'm in school and will share it with my classmates!
Glad it's helpful
It's really nice to understand the complex topics very easily.
Excellent explanation in 15 minutes..haven't seems such good explanation
Glad it helped Gopal. Cheers
Excellent content 👌 simple and contextual. keep up the awesome work
Thank you so much! Your videos are very helpful for me. Good to see that you have passed 100K+ subscribers.
Easy to understand, the way you've explained.
Wish I came across this channel earlier , nonetheless better late than never . Superb content and numbers shout that this channel is pretty underrated .
Beautifully explained and the use case was too good.
Glad it was helpful!
Thanks for the great Explanation with real time use cases
Glad it was helpful!
Thanks for the case studies. Quite helpful!
Excellent Presentation !! To the point and very clear !!
Thanks creator for making this video. 🙏
Ur videos are very informative. Thanks for your efforts
Many thanks. This video came at the exact right time for me.
Glad it was helpful!
wonderful content, very well explained, thanks!!
Glad you liked it!
Awesome and power-packed. Thanks for creating such beautiful content.
Awesome explanation.. Thanks
Very useful bro. Thanks a lot for this video!..
Glad it was helpful!
This was awesome
a precise and up to the point tutorial, great video.
Glad it was helpful!
Great explanation. Thank you
Well done , very well explained
Very good explanation. Thank you so much for coming up a nice presentation.
Glad it was helpful
After a long time good to watch the new tutorial.
#techprimers
Most awaiting
Thanks to upload this video. I was waiting for this content.
Hope you liked it!
@@TechPrimers alway ur welcome
Great vedio
Thank you sir 🙏
nice explanation
I was waiting for this video
Hope you are able to relate to real world entities
Thank you so much!
Thanks for the great video!!! Already subscribed!!
Clear explanation and awesome presentation... Thanks...
Glad it was helpful!
nice video content... hope your channel grow fast...
I hope so too :)
Thanks for your efforts this is the next level of learning on batch and stream process
my request could you please start a session on scala programming
Great video thanks a lot.
very good 👍
thorough explanation! great video, overall! thanks for all the info!
Precise and informative video... 👍🏻
Glad you liked it!
really superb. the way u hav explained the concept is beautifull. can u explain the spark architecture
Are you saying that Amazon Kinesis uses Apache Flink? As I understand, they have similar functionality, but Kinesis is proprietary while Flink is open source.
Thanks
thank you
can you make video of SpringBoot with Aws Lambda and Api Gateway of all crud operations
I have a video using Spring Boot, Lambda and api gateway
Good intro video
Thank you.
hey man, what software do you use to create these diagrams(like at 9:18)? Btw, great content as always!
Hi sir Could you please make the video on Rancher vs Openshift.
For realtime steam processing.
If i send each frame into my ML Inference load balanced servers as a post request, even this works right? Then why do we need kafka
Could we use spring streaming api instead of flink tô process the kinesis data analytics?
Hi Anderson,
Amazon Kinesis Data Analytics is a serverless offering which runs on ApacheFlink behind the scenes. We can integrate it to other AWS services, however we cannot use spring streaming inside data analytics
@@TechPrimers thank you for explanation :)
Excellent video ☺️. Can you please create a demo application for similar use case?
Thanks for the video. Could you please state why do we need to place analytics service before AWS streams? What should this service do in this particular example?
Maybe process and/or clean data and make it ingestable later
i would like to know if I have to synchronize 2 device with different time streams which technology can i use
this video is really helpful . can you please make video on concepts IBM MQ and avro kafka and Tibco etc . message queue and schema registration etc topics uses in scripting in performance testing and what are the goel to uses these concepts in scripting in performance testing with uses case examples to get proper visualization
so apache spark can do batch and also streaming processing ?
Regarding streaming, using all these services one by one, doesn't it caues lot of latency delay?
Hi @Tech Primers what is the difference between messaging and Streaming?..
This link has good explanation stackoverflow.com/questions/41744506/difference-between-stream-processing-and-message-processing
@@TechPrimers thanks 👍
You are my God :D
I'm still alive 🤷🏻♂️😁
Excellent explanation. sad to see few idiots dislike this video
Why can’t you get 100k subscribers...
That’s just a number Soy. The channel’s success is the quality and not the quantity.
Use cases are bit high standard to understand. Please take some easier ones.
too much information
wtf wrong with your micro, omfg
Thanks