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Airbyte: Open Source Data Integrations with Michel Tricot and John Lafleur

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Manage episode 288186887 series 1433319
Content provided by Open Source Archives - Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Open Source Archives - Software Engineering Daily 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://player.fm/legal.

ELT, or “Extract, Load, and Transform,” is the process that modern data pipelines use to replicate data from a source and load it into a target system such as a cloud data warehouse. ELT is a more flexible evolution of the traditional “Extract, Load, Transform” workflow used in pre-cloud systems. The power of ELT relies on flexible integrations between data sources and their targets, called connectors. The wide variety of data sources available to a cloud application today means that an ELT platform needs to handle a vast, and growing set of use cases for its connectors.

Airbyte is an open-source ELT platform built with the “long tail of integrations” in mind. Airbyte is secure, extensible, and simple to set up. Developers can use Airbyte’s platform to build the connectors they need for their specific use case, without worrying about scheduling, orchestrating, or monitoring.

Michel Tricot and John Lafleur are co-founders of Airbyte. Previously, Michel was Head of Integrations at Liveramp building data ingestion connectors, while John was the co-founder of StreamNation, Anaxi, and CEO of CodinGame. Michel and John join the show today to talk about why ELT has changed the way organizations manage and store their data, what technical challenges exist in the world of data integration, and how Airbyte can give your infrastructure “superpowers.”

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

The post Airbyte: Open Source Data Integrations with Michel Tricot and John Lafleur appeared first on Software Engineering Daily.

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143 episodes

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Manage episode 288186887 series 1433319
Content provided by Open Source Archives - Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Open Source Archives - Software Engineering Daily 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://player.fm/legal.

ELT, or “Extract, Load, and Transform,” is the process that modern data pipelines use to replicate data from a source and load it into a target system such as a cloud data warehouse. ELT is a more flexible evolution of the traditional “Extract, Load, Transform” workflow used in pre-cloud systems. The power of ELT relies on flexible integrations between data sources and their targets, called connectors. The wide variety of data sources available to a cloud application today means that an ELT platform needs to handle a vast, and growing set of use cases for its connectors.

Airbyte is an open-source ELT platform built with the “long tail of integrations” in mind. Airbyte is secure, extensible, and simple to set up. Developers can use Airbyte’s platform to build the connectors they need for their specific use case, without worrying about scheduling, orchestrating, or monitoring.

Michel Tricot and John Lafleur are co-founders of Airbyte. Previously, Michel was Head of Integrations at Liveramp building data ingestion connectors, while John was the co-founder of StreamNation, Anaxi, and CEO of CodinGame. Michel and John join the show today to talk about why ELT has changed the way organizations manage and store their data, what technical challenges exist in the world of data integration, and how Airbyte can give your infrastructure “superpowers.”

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

The post Airbyte: Open Source Data Integrations with Michel Tricot and John Lafleur appeared first on Software Engineering Daily.

  continue reading

143 episodes

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