Discover how OLAP data can transform your analytical processes and enhance insights. Learn practical applications and improve your data strategy today.

A walk-through on how to create an Airbyte DuckDB destination. All code changes are within a single PR for reference.

If you have already completed the official tutorial and the PokeAPI tutorial, and are looking to level up your connector development skills, then you are in

Use Octavia CLI to import, edit, and apply Airbyte application configurations.

Learn about the fundamental difference between a data warehouse and an operational database!

Here's the list of data sources and destinations that Airbyte supports: APIs, files, databases, APIs, data warehouses, data lakes, etc.

move(data) is celebrating the hard work and dedication of data engineers and practitioners worldwide! We’re hosting talks with speakers who have spent countless hours working on data movement.

Learn how to easily automate your LinkedIn Scraping with Airflow and Beautiful Soup in this recipe.

move(data) is celebrating the hard work and dedication of data engineers and practitioners worldwide! We’re hosting talks with speakers who have spent countless hours working on data movement.

Explains the open-source data lakes and their power with data lake table formats. What’s the difference between a lakehouse and when you need one.

Introductory post on Airbyte

Part 2 —  Extract and Load: Airbyte

git push your data stack with Airbyte, Airflow, and dbt - 2022 Airflow Summit - airbytehq/airflow-summit-airbyte-2022

Want to build a reliable, modern data architecture without the mess? Here’s a free checklist to help you → https://bit.ly/kds-checklist Airbyte is a data integration tool like Fivetran or Stitch, but completely open source! In today's video I want to show you how you can easily get started using it. While there are some limitations compared to the other products, in general Airbyte is incredibly powerful and will be sufficient for most use cases. They also have a cloud-hosted option that you can pay for if you don’t want to deal with the hassle of setting it up yourself. But by the end of this video, you'll be able to add this great product to your data engineering toolbox. Timestamps: 00:00 - Intro 01:32 - Install Docker 02:50 - Setup Airbyte via Docker 03:52 - Configure Source | Google Sheet 06:58 - Configure Destination | Snowflake 09:44 - Setup a Connection 12:18 - Load to a Different Schema 13:14 - Add a New Source & Connection Title & Tags: Getting Started w/ Airbyte! | Open Source Data Integration #kahandatasolutions #dataengineering #airbyte

Nearly every developer is familiar with creating a CLI. Containerized CLIs provide a flexible, cross-language standard with a low barrier to entry for open-source contributors. The ETL process can be reduced to two CLIs: one that reads data and one that writes data. While this interface is simple enough to implement from the contributor’s side, Kubernetes’ distributed nature means orchestrating data transfer between the CLIs on Kubernetes presents an unsolved problem. This talk describes a novel approach to reliably orchestrate CLIs on Kubernetes for data integration. Through this lens, we go through the evaluation of strategies and describe the pros and cons of each architecture for horizontally scaling containerised data integration workflows on Kubernetes. We also cover the journey of implementing a TCP-based “process” abstraction over CLIs using socat and UNIX pipes. This same approach powers all of Airbyte’s Kubernetes deployments and helps sync TBs of data daily. Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/

Explore the comparison of SQL vs. Python for data analysis, uncovering their strengths & weaknesses to guide your decision-making.