Zero - ETL ?

• AWS announced ETL-free integration between Aurora and Redshift, and between Redshift and Apache Spark
• Google announced the Zero-ETL approach with big Query
• Databricks announced direct queries on external systems using JDBC
• Microsoft Lake storage, in combination with Snowflake / Snowpipe, is close to the Zero-ETL approach

As Data Engineer, We well-know a question “What is Zero ETL”?

• So what is Zero ETL

So what is Zero ETL

• The Zero ETL is ideated to eliminate these problems by providing a secure way for data to move between different systems without any manual intervention. It ensures that all data is up-to-date through continuous federation between all connected systems.

• In Zero ETL, engineers will learn how to process data in the data lakes, lake houses, warehouses, or Spark clusters and Python scripts, so on, and they will rely on low-code platforms for many of their needs.

• This approach can be useful in situations where data needs to be transferred quickly and efficiently between systems, to enable near real-time analytics and machine learning (ML) without the need for complex data transformation or manipulation.

• With near real-time access to transactional data, you can leverage this for analytics and capabilities such as built-in ML, materialized views, data sharing, and federated access to multiple data stores and data lakes to derive insights from transactional and other data.