Delta Lake

What is Delta Lake?

A Delta Lake is an open-source storage layer designed to run on top of an existing data lake and improve its reliability, security, and performance. Delta Lakes support ACID transactions, scalable metadata, unified streaming, and batch data processing.

What does Delta Lake do?

Today’s companies generate massive amounts of data, which can be a valuable source of business intelligence and insight if it can be properly utilized. Delta Lake enables organizations to access and analyze new data in real time.

How does Delta Lake work?

Delta Lake adds a layer of intelligent data management and governance to an open storage environment for structured, semi-structured, and unstructured data, supporting both streaming and batch operations from a single source. 

What are the features and benefits of Delta Lake?

Open format: Delta Lake uses the open source Apache Parquet format and is fully compatible with the Apache Spark unified analytics engine for powerful, flexible operations.

ACID transactions: Delta Lake enables ACID (atomicity, consistency, isolation, durability) transactions for Big Data workloads. It captures all changes made to the data in a serialized transaction log, protecting the data’s integrity and reliability and providing full, accurate audit trails.

Time travel: Delta Lake’s transaction log provides a master record of every change made to the data, which makes it possible to recreate the exact state of a data set at any point in time. Data versioning makes data analyses and experiments completely reproducible.

Schema enforcement: Delta Lake protects the quality and consistency of your data with robust schema enforcement, ensuring that data types are correct and complete and preventing bad data from corrupting critical processes.

Merge, update, delete: Delta Lake supports data manipulation language (DML) operations including merge, update, and delete commands for compliance and complex use cases such as streaming upserts, change-data-capture, slowly-changing-dimension (SCD) operations, and more. 

Delta Lakes vs. data lakes vs. warehouses

A delta Lake combines the advantages of data lakes and data warehouses to create a scalable, cost-effective data lakehouse. Learn about delta lakes vs. data lakes, data lakehouses vs. data warehouses.

Delta Lake

A delta lake, an evolution of data storage,  preserves the integrity of your original data without sacrificing the performance and agility required for real-time analytics, artificial intelligence (AI), and machine learning (ML) applications.

Data Lake

A data lake is a massive accumulation of raw data in multiple formats. The sheer volume and variety of information in a data lake can make analysis cumbersome and, without auditing or governance, the quality and consistency of the data can be unreliable.

Data Lakehouse

A data lakehouse combines the flexibility and scalability of a data lake with the structure and management features of a data warehouse in a simple, open platform. 

Data Warehouse

A data warehouse gathers information from multiple sources, then reformats and organizes it into a large, consolidated volume of structured data that’s optimized for analysis and reporting. Proprietary software and an inability to store unstructured data can limit its usefulness.

HPE and Delta Lake

HPE GreenLake edge-to-cloud platform is built on HPE Ezmeral software and optimized for Kubernetes-based Apache Spark analytics with Delta Lake integration.

HPE Ezmeral and Apache Spark 3.0 with Delta Lake provide reliable and consistent data for business analytics and machine learning applications. Kubernetes-based cluster orchestration enables dynamic scaling for data-intensive workloads.

HPE Ezmeral Runtime offers industry-leading cluster and application management for physical and cloud-based infrastructures.

HPE Ezmeral Data Fabric elevates data management and tenant storage.