10 Powerful Features to Simplify Semi-structured Data Management in the Databricks Lakehouse
Hassle Free Data IngestionDiscover how Databricks simplifies semi-structured data ingestion into Delta Lake with detailed use cases, a demo, and live Q&A. WATCH NOW Ingesting and querying JSON with semi-structured data can be tedious and time-consuming, but Auto Loader and Delta Lake make it easy. JSON data is very flexible, which makes it powerful, but...
How Incremental ETL Makes Life Simpler With Data Lakes
Incremental ETL (Extract, Transform and Load) in a conventional data warehouse has become commonplace with CDC (change data capture) sources, but scale, cost, accounting for state and the lack of machine learning access make it less than ideal. In contrast, incremental ETL in a data lake hasn’t been possible due to factors such as the...
Getting Started With Ingestion into Delta Lake
Ingesting data can be hard and complex since you either need to use an always-running streaming platform like Kafka or you need to be able to keep track of which files haven’t been ingested yet. In this blog, we will discuss Auto Loader and COPY INTO, two methods of ingesting data into a Delta Lake...
How to Simplify CDC With Delta Lake’s Change Data Feed
Try this notebook in Databricks Change data capture (CDC) is a use case that we see many customers implement in Databricks – you can check out our previous deep dive on the topic here. Typically we see CDC used in an ingestion to analytics architecture called the medallion architecture. The medallion architecture that takes...
Simplifying Streaming Stock Analysis using Delta Lake and Apache Spark: On-Demand Webinar and FAQ Now Available!
On June 13th, we hosted a live webinar — Simplifying Streaming Stock Analysis using Delta Lake and Apache Spark — with Junta Nakai, Industry Leader - Financial Services at Databricks, John O’Dwyer, Solution Architect at Databricks, and Denny Lee, Technical Product Marketing Manager at Databricks. This is the first webinar in a series of financial...
Simplify Streaming Stock Data Analysis Using Databricks Delta
Traditionally, real-time analysis of stock data was a complicated endeavor due to the complexities of maintaining a streaming system and ensuring transactional consistency of legacy and streaming data concurrently. Databricks Delta Lake helps solve many of the pain points of building a streaming system to analyze stock data in real-time. In the following diagram, we...
