AWS Database Blog
Secure your data with Amazon RDS for SQL Server: A guide to best practices and fortification
Securing SQL Server databases in the cloud is critical, and Amazon Relational Database Service for SQL Server (Amazon RDS) provides several security features to help ensure the confidentiality, integrity, and availability of your database instances. These features include data encryption at rest and in transit, secure user authentication and authorization mechanisms, network isolation, and fine-grained […]
Choose the right Amazon RDS deployment option: Single-AZ instance, Multi-AZ instance, or Multi-AZ database cluster
In addition to offering you a choice of seven well-known engines, Amazon Relational Database Service (Amazon RDS) also offers a number of deployment choices to assist you in selecting the option that best suits your workload. You can evaluate your requirements and then choose the right set of service offerings. In the latest set of […]
Build a knowledge graph on Amazon Neptune with AI-powered video analysis using Media2Cloud
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 […]
Joining historical data between Amazon Athena and Amazon RDS for PostgreSQL
While databases are used to store and retrieve data, there are situations where applications should archive or purge the data to reduce storage costs or improve performance. However, there are often business requirements where an application must query both active data and archived data simultaneously. Developers need a solution that lets them benefit from using […]
Working with JSON data in Amazon DynamoDB
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 […]
Security is time series: How VMware Carbon Black improves and scales security observability with Amazon Timestream
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 […]
Achieve a high-performance migration to Amazon RDS for Oracle from on-premises Oracle with AWS DMS
Many customers deploy the Oracle Database to an on-premises data centers running general purpose hardware or a highly customized Oracle Exadata hardware. These Oracle database customers are now looking to migrate to Amazon Relational Database Service (Amazon RDS) for Oracle, which is a fully managed commercial database that makes it easy to set up, operate, […]
Optimize costs by scheduling provisioned capacity for Amazon DynamoDB
Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB charges for reading, writing, and storage of your DynamoDB tables, along with any optional features you choose to enable. When you create a DynamoDB table, you choose from two capacity modes that have different billing options […]
Deploy schema changes in an Amazon Aurora MySQL database with minimal downtime
Modifying the schema of a SQL database can be time-consuming, resource-intensive, and error-prone. It can also require long periods of downtime that negatively affects the end-user experience. In this post, I walk you through performing schema changes using Instant DDL and Amazon Relational Database Service (Amazon RDS) Blue/Green Deployments for Amazon Aurora MySQL-Compatible Edition with […]
Migrate billions of records from an Oracle data warehouse to Amazon Redshift using AWS DMS
Customers are migrating to Amazon Redshift to modernize their data warehouse solution and help save on their licensing, support, operations, and maintenance costs. To migrate data from an on-premises data warehouse to Amazon Redshift, you can use services such as AWS Database Migration Service (AWS DMS), AWS Schema Conversion Tool (AWS SCT), Amazon Simple Storage […]