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Streaming Caffeine E3: Yaroslav(Goldsky) and Jove(Timeplus)

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Manage episode 376867875 series 3511111
Content provided by Jove Zhong. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jove Zhong or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Welcome to the latest episode of Streaming Cafe with your host, Jove!

In this exciting interview, Jove is joined by a special guest, Yarosalv, Principal Software Engineer at Goldsky, to delve into the realm of data streaming, engineering challenges, and real-world experiences.

Timestamps:

00:00:00 Welcome Yarosalv00:01:40 Yaroslav self-intro, Activision, Shopify, Goldsky

00:04:00 Yaroslav talk on Current23 and other talks he recommends00:14:20 Jove’s talk on Current23

00:16:00 Yaroslav blog00:18:40 Blog writing on Friday00:21:00 data streaming, streaming ETL

00:29:00 streaming vs batch, OLAP, CBO, JOIN, new challenges

00:36:00 data democratization, real-time insights for everyone, not just executives

00:36:55 data app vs data product00:39:10 next-gen AI is coming a data problem, Tesla e2e FSD v12

00:41:00 blockchain is a distributed app platform, late events in web3

00:50:00 tech community in Vancouver00:56:40 VLDB, Feldera, Materialize

01:00:17 data streaming in depth is not easy. How about streaming databases

Yaroslav's talk on Current23 and other talks he recommends

* Dynamic Change Data Capture with Flink CDC and Consistent HashingKeynote

* Restate: Stream Processing, but for Microservices

* Isolating Streaming Ingest and Queries Using RocksDB (Rockset)

* Deeply Declarative Data Pipelines (LinkedIn, Ryanne Dolan)

* Off-Label Data Mesh: A Prescription for Healthier Data (Confluent, Adam Bellemare)

* Learnings of Running Kafka Tiered Storage at Scale (Uber)

* Evolution of Streaming Pipeline at Lyft (Lyft)* Why Serverless Flink Matters - Blazing Fast Stream Processing Made Scalable (Confluent)

* Query Your Streaming Data on Kafka using SQL: Why, How, and What (Timeplus)

  continue reading

8 episodes

Artwork
iconShare
 
Manage episode 376867875 series 3511111
Content provided by Jove Zhong. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jove Zhong or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Welcome to the latest episode of Streaming Cafe with your host, Jove!

In this exciting interview, Jove is joined by a special guest, Yarosalv, Principal Software Engineer at Goldsky, to delve into the realm of data streaming, engineering challenges, and real-world experiences.

Timestamps:

00:00:00 Welcome Yarosalv00:01:40 Yaroslav self-intro, Activision, Shopify, Goldsky

00:04:00 Yaroslav talk on Current23 and other talks he recommends00:14:20 Jove’s talk on Current23

00:16:00 Yaroslav blog00:18:40 Blog writing on Friday00:21:00 data streaming, streaming ETL

00:29:00 streaming vs batch, OLAP, CBO, JOIN, new challenges

00:36:00 data democratization, real-time insights for everyone, not just executives

00:36:55 data app vs data product00:39:10 next-gen AI is coming a data problem, Tesla e2e FSD v12

00:41:00 blockchain is a distributed app platform, late events in web3

00:50:00 tech community in Vancouver00:56:40 VLDB, Feldera, Materialize

01:00:17 data streaming in depth is not easy. How about streaming databases

Yaroslav's talk on Current23 and other talks he recommends

* Dynamic Change Data Capture with Flink CDC and Consistent HashingKeynote

* Restate: Stream Processing, but for Microservices

* Isolating Streaming Ingest and Queries Using RocksDB (Rockset)

* Deeply Declarative Data Pipelines (LinkedIn, Ryanne Dolan)

* Off-Label Data Mesh: A Prescription for Healthier Data (Confluent, Adam Bellemare)

* Learnings of Running Kafka Tiered Storage at Scale (Uber)

* Evolution of Streaming Pipeline at Lyft (Lyft)* Why Serverless Flink Matters - Blazing Fast Stream Processing Made Scalable (Confluent)

* Query Your Streaming Data on Kafka using SQL: Why, How, and What (Timeplus)

  continue reading

8 episodes

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