Remove Data Lake Remove Optimization Remove Snapshot
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Manage concurrent write conflicts in Apache Iceberg on the AWS Glue Data Catalog

AWS Big Data

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. We will also cover the pattern with automatic compaction through AWS Glue Data Catalog table optimization.

Snapshot 137
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Use open table format libraries on AWS Glue 5.0 for Apache Spark

AWS Big Data

Open table formats are emerging in the rapidly evolving domain of big data management, fundamentally altering the landscape of data storage and analysis. By providing a standardized framework for data representation, open table formats break down data silos, enhance data quality, and accelerate analytics at scale.

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Build a high-performance quant research platform with Apache Iceberg

AWS Big Data

Iceberg offers distinct advantages through its metadata layer over Parquet, such as improved data management, performance optimization, and integration with various query engines. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

Metadata 111
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The AWS Glue Data Catalog now supports storage optimization of Apache Iceberg tables

AWS Big Data

The AWS Glue Data Catalog now enhances managed table optimization of Apache Iceberg tables by automatically removing data files that are no longer needed. Iceberg creates a new version called a snapshot for every change to the data in the table. As more table changes are made, more data files are created.

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

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. and later supports the Apache Iceberg framework for data lakes. The snapshot points to the manifest list. AWS Glue 3.0

Data Lake 137
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How Cloudinary transformed their petabyte scale streaming data lake with Apache Iceberg and AWS Analytics

AWS Big Data

Cloudinary is a cloud-based media management platform that provides a comprehensive set of tools and services for managing, optimizing, and delivering images, videos, and other media assets on websites and mobile applications.

Data Lake 126
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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

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.

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