Category: Intermediate (200)

A knowledge graph allows us to combine data from different sources to gain a better understanding of a specific problem domain. In this post, we use Amazon Neptune (a managed graph database service) to create a knowledge graph about technology products. In addition to the data we already have in the graph, we add the […]

Amazon DynamoDB allows you to store JSON objects into attributes and perform many operations on these objects, including filtering, updating, and deleting. This is a very powerful capability because it allows applications to store objects (JSON data, arrays) directly into DynamoDB tables, and still retain the ability to use nested attributes within these objects in […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Amazon Timestream is a fast, serverless, and secure time series database and analytics service that can scale to process trillions of time series events per day. Organizations […]

Many customers use AWS Backup to automatically create Amazon Relational Database Service (Amazon RDS and Aurora) database snapshots. RDS database snapshots are a convenient way to protect your data and make it easy to recover in the event of an accident or disaster. If you’re using RDS Snapshots for long-term archival to meet compliance requirements […]

In this post, we discuss how DevOcean uses Amazon Neptune to power its cloud application vulnerability remediation platform. The DevOcean platform provides a unified dashboard to manage security events across all the layers of a customer’s cloud applications. With DevOcean, users can prioritize risk, reduce alert fatigue, and manage remediation faster with appropriate owners within […]

AWS launched Amazon Database Migration Accelerator (Amazon DMA) to accelerate your journey to AWS databases and analytics services and achieve cloud adoption benefits such as cost savings and performance improvements. Amazon DMA has assisted thousands of customers globally to migrate their workloads (database and application) to AWS databases and analytics services. In this post, we […]

Global tables build on the global Amazon DynamoDB footprint to provide you with a fully managed, multi-Region, multi-active database that delivers fast, local, read and write performance for massively scaled, global applications. Global tables replicate your DynamoDB tables automatically across your choice of AWS Regions. DynamoDB Shell is an interactive command line interface for DynamoDB. […]

Amazon DynamoDB uses horizontal scaling to support tables of virtually any size. In addition to horizontal scaling, DynamoDB provides single-digit millisecond performance for workloads of all sizes. Retail sites like Amazon.com use DynamoDB for their shopping carts and workflow engines. A slow response while processing an order can not only be frustrating to customers, but […]

Most database engines log error messages, warnings, traces, and audit statements. Database observability and monitoring are achieved by tracking this log information and taking proactive and reactive actions, such as allocating space when it is low, or stopping sessions causing exclusive locks or connection storms. In Amazon Relational Database Service (Amazon RDS) for Oracle, alert […]

In March 2022, we introduced a new Multi-AZ deployment option for Amazon Relational Database Service (Amazon RDS) for PostgreSQL, called Multi-AZ DB clusters. This deployment option increases read capacity with two readable standby instances, and improves write transaction latency and failover times. The optimization of transaction latency uses local storage on purpose-built Amazon Elastic Compute […]