Why Databricks Delta Live Tables?

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Bryan Cafferky

Bryan Cafferky

Күн бұрын

Пікірлер: 26
@raghuramsharma2603
@raghuramsharma2603 Жыл бұрын
Hi Bryan, thanks for all the hard work you are putting in to make these videos...Can you pls upload a video about Unity Catalog which is a new evolution on Databricks. Thanks
@BryanCafferky
@BryanCafferky Жыл бұрын
It's on my list but could get a bit costly since I have to pay for the Azure services out of pocket and Unity Catalog is a multi workspace solution.
@raghuramsharma2603
@raghuramsharma2603 Жыл бұрын
@@BryanCafferky thanks for replying Bryan we are currently performing a POC at our client location on unity+ lakehouse.
@gardnmi
@gardnmi Жыл бұрын
Hopefully, one day, you'll get to talk about the move away from the jvm in your timeline.
@naumanshah2597
@naumanshah2597 Жыл бұрын
Bryan - I'm here just for the way you pose the question with that face you make :-D Love it! Always makes me imagine a class of little dwarfs sitting looking up to you and throwing those questions at you :-D Keep going ma man! God bless you!
@ngneerin
@ngneerin Жыл бұрын
Need tutorial on terraform for databricks+AWS multiple workspaces and unity catalog
@clapathy
@clapathy Жыл бұрын
Thanks Brian for the video. I've been usin delta live tables and pipelines for a while and haven't find them as useful TBH. The main disadvantage is that they are proprietary, hence bring a lot of limitations, - you can not set up the environment in which you run you code is the biggest pain - you can't appropriately unit test you code that you send to databricks - you don't have a proper access and understanding of what is running behind the scenes when databricks sets up the pipeline and tables I know that you can come up with hacky solutions to deal with these downsides, but in the end I found it easier and more transparent to code up manually the things you mentioned as pros. (managing checkpoints, triggering, great expectations)
@BryanCafferky
@BryanCafferky Жыл бұрын
Ok. Bear in mind, Databricks is investing a lot in DLT and the current limitations are likely short term. Granular control means more work. In the long run, not moving to DTL may mean you lose out on future new features. But yes, there are some limitations. Thanks for your comments!
@jasjyotsingh2007
@jasjyotsingh2007 Жыл бұрын
Completely agree , the development on Delta Live Tables is not as intuitive
@ahmedtrifa8902
@ahmedtrifa8902 11 ай бұрын
Very intersting approach to introduce DLT by puting it in the context of Scaled Out architecture. Thanks !
@paulroy9639
@paulroy9639 Жыл бұрын
Superb Explanation .... became your fan 😀
@howardlevenson
@howardlevenson 11 ай бұрын
Great explanation of DLT. I particularly liked the feature call out at the end.
@cseveer
@cseveer Жыл бұрын
Thanks Bryan, as always crystal-clear explanation.
@gurramvarunchowdary5735
@gurramvarunchowdary5735 Жыл бұрын
Hi Bryan, I wanna do the DML operation the delta tables. Will there be any use if i go for delta live tables instead of just delta tables? Note that these DML happens in batch wise not streaming. I have a feeling not to use delta live because i am not doing any kinda inter-dependency taks between tables liek a pipeline instead i am running a set of DML. Also i am feeling a bit to use delta live because of it's auto maintanence. What are your views on this? Please help me out!!
@sarahweatherbee5829
@sarahweatherbee5829 Жыл бұрын
I love your videos. Keep up the good work! 😊
@tanushreenagar3116
@tanushreenagar3116 Жыл бұрын
superb explanation
@stu8924
@stu8924 Жыл бұрын
Thank you Bryan
@tensefragile5242
@tensefragile5242 Жыл бұрын
I love how you ask questions to yourself with a funny voice and then answer them
@OpenR3
@OpenR3 Жыл бұрын
Great content
@avecNava
@avecNava Жыл бұрын
So Live tables are smart autonomous tables ;)
@BryanCafferky
@BryanCafferky Жыл бұрын
Subject to the magic of DLT.
Жыл бұрын
Oh so now everything is Databricks like the era of Cloudera for Hadoop. I'm sure it won't create any issue like it happend for Cloudera.
@BryanCafferky
@BryanCafferky Жыл бұрын
The only difference is success. SQL Server has been successful for 40+ years. Databricks created Apache Spark and are the largest open source contributor. I think they will be just fine. Of course, when to use any platform is dependent upon your requirements.
Жыл бұрын
@@BryanCafferky I do have a problem since with this, especially being so closed to a framework that can decide to raise up the cost of using it whenever they want.
@BryanCafferky
@BryanCafferky Жыл бұрын
@ A good alterative is dbt. You can so many of the same things and there is an open source version.
@fb-gu2er
@fb-gu2er Жыл бұрын
Tell me nothing by saying a lot
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