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

AWS Big Data

This post focuses on introducing an active-passive approach using a snapshot and restore strategy. Snapshot and restore in OpenSearch Service The snapshot and restore strategy in OpenSearch Service involves creating point-in-time backups, known as snapshots , of your OpenSearch domain.

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Implement disaster recovery with Amazon Redshift

AWS Big Data

With built-in features such as automated snapshots and cross-Region replication, you can enhance your disaster resilience with Amazon Redshift. Amazon Redshift supports two kinds of snapshots: automatic and manual, which can be used to recover data. Snapshots are point-in-time backups of the Redshift data warehouse.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

In addition to driving operational efficiency and consistently meeting fulfillment targets, logistics providers use big data applications to provide real-time updates as well as a host of flexible pick-up, drop-off, or ordering options.

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Radically Reduce Downtime and Data Loss with SaaS-based Disaster Recovery

CIO Business Intelligence

Compare it to traditional backup and snapshots, which entail scheduling, agents, and impacts to your production environment. Zerto uses block-level replication, so each change is copied at the hypervisor level without a need for agents, snapshots, or scheduled maintenance. Disaster Recovery, HPE, IT Leadership

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How Amazon GTTS runs large-scale ETL jobs on AWS using Amazon MWAA

AWS Big Data

During the upgrade process, Amazon MWAA captures a snapshot of your environment metadata; upgrades the workers, schedulers, and web server to the new Airflow version; and finally restores the metadata database using the snapshot, backing it with an automated rollback mechanism.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

The following figure shows a daily query volume snapshot (queries per day and queued queries per day, which waited a minimum of 5 seconds). Redshift Test Drive also provides additional features such as a self-hosted analysis UI and the ability to replicate external objects that a Redshift workload may interact with.

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Build a data lake with Apache Flink on Amazon EMR

AWS Big Data

salesdb.sql Connect to the RDS for MySQL database and run the salesdb.sql command to initialize the database, providing the host name and user name according to your RDS for MySQL database configuration: mysql -h -u -p mysql> source salesdb.sql Create an EMR cluster with the AWS Glue Data Catalog From Amazon EMR 6.9.0,