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Delta Lake - Delta Tablesa
Azure Analytics
Mar 29, 2023 10:00 PM

Delta Lake - Delta Tablesa

by HubSite 365 about Pragmatic Works

Data AnalyticsAzure AnalyticsM365 Hot News

Have you heard of a Delta Lake? What is up with that? In this second video in our new series on Delta Lake, Austin goes through the basics of explaining what a

Have you heard of a Delta Lake? What is up with that? In this second video in our new series on Delta Lake, Austin goes through the basics of explaining what a delta is, how to store data in the data lake using delta, working with the transaction log, and querying the delta table with serverless SQL On-Demand in Azure Synapse Analytics.

Delta tables are a type of data storage format used in Apache Spark. They are optimized for data streaming and provide a better solution for maintaining a large data set over time. Delta tables store data in Apache Parquet format, a columnar storage format that is optimized for analytics. Delta tables provide features such as time travel, transaction isolation, and automatic compaction. They also support ACID transactions, which allow users to make changes to the tables without impacting other users. Delta tables are a great solution for data processing and analytics on big data sets.

Tutorial · ‎Delta table properties reference · ‎Table streaming reads and... · ‎Optimize

Documentation · ‎Delta Sharing · ‎Contributing to Delta · ‎Delta Lake Merge

What is Databricks? · ‎What is the Need for... · ‎Databricks Delta a

Mar 15, 2023 — Delta Lake is the optimized storage layer that provides the foundation for storing data and tables in the Databricks Lakehouse Platform.

7 key moments in this video

Nov 14, 2022 — Delta's time travel capabilities in Azure Databricks simplify building data pipelines for the above challenges. As you write into a Delta table ...

The geodatabase system tables that record version changes are referred to as the delta tables. For each table or feature class that has been versioned, two new ...

#1: Caching · ‎#2: Time Travel · ‎#3: Merging Datasets