Dumb Down Azure Databricks Delta Lake Architecture

In this modern data world, the importance of data has been increased exponentially and organizations are spending a vast amount of time and money on the new technologies that allow firms to quickly process and make a good sense of the data.

With the increased volume of the data, data processing ( ETL-Extract Transform and Load or ELT -Extract Load and Transform) and analysis (data analytics, data science, and machine learning) is becoming more and more time-consuming and companies are looking beyond the traditional data architectures to meet theirs on-demand analytical needs.

Delta Lake is one such solution that provides a massive improvement over traditional data architectures. It is an open-source storage layer that provides ACID transactions and metadata handling. It also unifies batch data and streaming data for building near-real-time analytics.

Here are a few key advantages of Delta Lake

• Handles high volume of data (terabytes or even petabytes) with ease
• Unified Batch and Stream processing with ACID (Atomicity, Consistency, Isolation, Durability) transactions
• Delta allows data writers to do Delete, Update, and Upsert very easily without interfering with the scheduled jobs reading the data set
• Delta records each and every action that is performed on a delta lake table since its creation. This enables the users to query an older snapshot of the data (time travel or data versioning)
• Delta Enforces the Schema and prevents bad writing…