AWS Database Blog
Author: Dhiraj Thakur
Dhiraj Thakur is a Solutions Architect with Amazon Web Services. He works with AWS customers and partners to provide guidance on enterprise cloud adoption, migration, and strategy. He is passionate about technology and enjoys building and experimenting in the analytics and AI/ML space.
Supply chain data analysis and visualization using Amazon Neptune and the Neptune workbench
Many global corporations are managing multiple supply chains, and they depend on those operations to not only deliver goods on time but to respond to divergent customer and supplier needs. According to a McKinsey study, it’s estimated that significant disruptions to production now occur every 3.7 years on average, adding new urgency to supply chain […]
Set up scheduled backups for Amazon DynamoDB using AWS Backup – Part 2
Amazon DynamoDB offers two types of backups: point-in-time recovery (PITR) and on-demand backups. PITR is used to recover your table to any point in time in a rolling 35 day window, which is used to help customers mitigate accidental deletes or writes to their tables from bad code, malicious access, or user error. On demand […]
Enhanced AWS Backup features for Amazon DynamoDB
Amazon Web Services (AWS) recently announced new features in AWS Backup for Amazon DynamoDB on-demand backups that can help you meet your compliance, business continuity, and cost-optimization needs. In this post, we describe these features and provide a step-by-step guide for using them to copy DynamoDB backups across AWS Regions and across accounts, configure your […]
Set up scheduled backups for Amazon DynamoDB using AWS Backup
With customers scaling up their AWS workloads across hundreds, if not thousands of AWS resources, customers have expressed the need to centrally manage and monitor their backups. They want to have a standardized way to manage their backups at scale. AWS Backup enables you to centralize and automate data protection across AWS services. AWS Backup […]
Build an Amazon Keyspaces (for Apache Cassandra) data model using NoSQL Workbench
In this post, we build an end-to-end data model for an internet data consumption application. Data modeling provides a means of planning and blueprinting the complex relationship between an application and its data. Creating an efficient data model helps to achieve better query performance. An inefficient data model can slow development and performance, increase costs, […]