Data Engineering Podcast

En podcast av Tobias Macey - Söndagar

Söndagar

Kategorier:

419 Avsnitt

  1. TimescaleDB: Fast And Scalable Timeseries with Ajay Kulkarni and Mike Freedman - Episode 18

    Publicerades: 2018-02-11
  2. Pulsar: Fast And Scalable Messaging with Rajan Dhabalia and Matteo Merli - Episode 17

    Publicerades: 2018-02-04
  3. Dat: Distributed Versioned Data Sharing with Danielle Robinson and Joe Hand - Episode 16

    Publicerades: 2018-01-29
  4. Snorkel: Extracting Value From Dark Data with Alex Ratner - Episode 15

    Publicerades: 2018-01-22
  5. CRDTs and Distributed Consensus with Christopher Meiklejohn - Episode 14

    Publicerades: 2018-01-15
  6. Citus Data: Distributed PostGreSQL for Big Data with Ozgun Erdogan and Craig Kerstiens - Episode 13

    Publicerades: 2018-01-08
  7. Wallaroo with Sean T. Allen - Episode 12

    Publicerades: 2017-12-25
  8. SiriDB: Scalable Open Source Timeseries Database with Jeroen van der Heijden - Episode 11

    Publicerades: 2017-12-18
  9. Confluent Schema Registry with Ewen Cheslack-Postava - Episode 10

    Publicerades: 2017-12-10
  10. data.world with Bryon Jacob - Episode 9

    Publicerades: 2017-12-03
  11. Data Serialization Formats with Doug Cutting and Julien Le Dem - Episode 8

    Publicerades: 2017-11-22
  12. Buzzfeed Data Infrastructure with Walter Menendez - Episode 7

    Publicerades: 2017-11-14
  13. Astronomer with Ry Walker - Episode 6

    Publicerades: 2017-08-06
  14. Rebuilding Yelp's Data Pipeline with Justin Cunningham - Episode 5

    Publicerades: 2017-06-18
  15. ScyllaDB with Eyal Gutkind - Episode 4

    Publicerades: 2017-03-18
  16. Defining Data Engineering with Maxime Beauchemin - Episode 3

    Publicerades: 2017-03-05
  17. Dask with Matthew Rocklin - Episode 2

    Publicerades: 2017-01-22
  18. Pachyderm with Daniel Whitenack - Episode 1

    Publicerades: 2017-01-14
  19. Introducing The Show - Episode 0

    Publicerades: 2017-01-08

21 / 21

This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

Visit the podcast's native language site