Delta Lake is an open-source storage layer that brings reliability to data lakes. It is built on top of Apache Parquet and provides ACID (Atomicity, Consistency, Isolation, Durability) transactions, which ensure data integrity and reliability even in the case of system failures or errors.

Delta Lake also integrates with big data processing frameworks such as Apache Spark and Apache Hive, making it easy to use for big data analytics and machine learning workflows.

Additionally, Delta Lake supports schema evolution, so data engineers and data scientists can continue to make changes to the schema of a Delta table even after data has been written to it, making it easier to work with evolving data sources.

Why do we need Delta Lake?

Delta Lake is a data storage layer that provides several benefits over traditional data storage solutions. It offers ACID transactions, version control, schema enforcement, and data indexing, which enable efficient data management, improved data quality, and more reliable data processing.

Delta Lake can help organizations better manage and analyze large volumes of data in a scalable and efficient way, making it a valuable tool for data engineering and data analytics tasks.