AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 112

Data Lake Data Warehouse Visualization Snapshot 112

AWS Big Data

APRIL 3, 2024

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

Data Lake 94

Data Lake Snapshot Metadata Data Architecture 94

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

Data Lake 74

Data Lake Snapshot Optimization Data Transformation 74

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. It allows us to independently upgrade the Virtual Warehouses and Database Catalogs.

Data Warehouse 82

Data Warehouse Snapshot Metadata Cost-Benefit 82

AWS Big Data

MARCH 2, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. In early 2022, AWS announced general availability of Athena ACID transactions, powered by Apache Iceberg. and later supports the Apache Iceberg framework for data lakes.

Data Lake 118

Data Lake Data Processing Metadata Snapshot 118

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

AWS Big Data

JUNE 21, 2023

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 80

Data Warehouse Data Lake OLAP Cost-Benefit 80