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Achieve data resilience using Amazon OpenSearch Service disaster recovery with snapshot and restore

AWS Big Data

Disaster recovery is vital for organizations, offering a proactive strategy to mitigate the impact of unforeseen events like system failures, natural disasters, or cyberattacks. In Disaster Recovery (DR) Architecture on AWS, Part I: Strategies for Recovery in the Cloud , we introduced four major strategies for disaster recovery (DR) on AWS.

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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. The Data Catalog provides the functionality as the Iceberg catalog. Determine the changes in transaction, and write new data files.

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Build a high-performance quant research platform with Apache Iceberg

AWS Big Data

In our previous post Backtesting index rebalancing arbitrage with Amazon EMR and Apache Iceberg , we showed how to use Apache Iceberg in the context of strategy backtesting. Our analysis shows that Iceberg can accelerate query performance by up to 52%, reduce operational costs, and significantly improve data management at scale.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

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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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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

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

AWS Big Data

A modern data strategy redefines and enables sharing data across the enterprise and allows for both reading and writing of a singular instance of the data using an open table format.

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