What is — Delta Lake

Delta Lake, a project initially developed by Databricks and later open-sourced, is a robust storage layer that brings ACID transactions to Apache Spark and big data workloads. It is designed to improve data reliability and simplify data management in data lakes. Here’s a more detailed look at Delta Lake and guidance on how to get started.

Key Features of Delta Lake

ACID Transactions: Ensures data integrity with atomic, consistent, isolated, and durable transactions, even in the face of failures.

Scalable Metadata Handling: Efficiently handles metadata for large tables with millions of files, which is a challenge in traditional data lakes.

Schema Enforcement and Evolution: Automatically checks and enforces schema during write operations and allows for safe and controlled changes to the schema.

Time Travel (Data Versioning): Allows you to query previous versions of the data for audit purposes, rollbacks, or reproducing experiments.

Unified Batch and Streaming Source and Sink: A table in Delta Lake is both a batch table and a streaming source and sink, streamlining both batch and real-time data processing.

Upserts and Deletes: Supports complex operations like updates, deletes, and merges into tables, making it easier to manage and clean data.