⏱ 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 .
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
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
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
It's hard to find quality content about advanced topics like this. Well explained 👍
Glad it was helpful!
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?
This video was thorough, clear, and very helpful, thanks!! I'm in school and will share it with my classmates!
Glad it's helpful
Excellent explanation in 15 minutes..haven't seems such good explanation
Glad it helped Gopal. Cheers
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.
It's really nice to understand the complex topics very easily.
Thanks for the great Explanation with real time use cases
Glad it was helpful!
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 the case studies. Quite helpful!
wonderful content, very well explained, thanks!!
Glad you liked it!
Excellent content 👌 simple and contextual. keep up the awesome work
Ur videos are very informative. Thanks for your efforts
Beautifully explained and the use case was too good.
Glad it was helpful!
Very useful bro. Thanks a lot for this video!..
Glad it was helpful!
Excellent Presentation !! To the point and very clear !!
Many thanks. This video came at the exact right time for me.
Glad it was helpful!
Thanks creator for making this video. 🙏
Awesome explanation.. Thanks
Awesome and power-packed. Thanks for creating such beautiful content.
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 to upload this video. I was waiting for this content.
Hope you liked it!
@@TechPrimers alway ur welcome
This was awesome
After a long time good to watch the new tutorial.
#techprimers
Great explanation. Thank you
Thank you sir 🙏
Great vedio
a precise and up to the point tutorial, great video.
Glad it was helpful!
Thank you so much!
Thanks for the great video!!! Already subscribed!!
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
Most awaiting
Very good explanation. Thank you so much for coming up a nice presentation.
Glad it was helpful
Well done , very well explained
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
nice explanation
I was waiting for this video
Hope you are able to relate to real world entities
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
Regarding streaming, using all these services one by one, doesn't it caues lot of latency delay?
Clear explanation and awesome presentation... Thanks...
Glad it was helpful!
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 :)
i would like to know if I have to synchronize 2 device with different time streams which technology can i use
so apache spark can do batch and also streaming processing ?
really superb. the way u hav explained the concept is beautifull. can u explain the spark architecture
Great video thanks a lot.
very good 👍
Hi sir Could you please make the video on Rancher vs Openshift.
thank you
Precise and informative video... 👍🏻
Glad you liked it!
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 👍
thorough explanation! great video, overall! thanks for all the info!
Good intro video
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
hey man, what software do you use to create these diagrams(like at 9:18)? Btw, great content as always!
Thank you.
Thanks
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
Excellent video ☺️. Can you please create a demo application for similar use case?
You are my God :D
I'm still alive 🤷🏻♂️😁
Excellent explanation. sad to see few idiots dislike this video
Use cases are bit high standard to understand. Please take some easier ones.
Why can’t you get 100k subscribers...
That’s just a number Soy. The channel’s success is the quality and not the quantity.
too much information
wtf wrong with your micro, omfg
Thanks