AWS Database Blog

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 […]

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 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, […]

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 […]

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 […]

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 […]

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server is a managed database service for legacy, custom, and packaged applications that require access to the underlying operating system and database (DB) environment. It helps automate the setup, operation, and scaling of databases in the cloud while granting access to the database and underlying operating […]

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 […]

Migrating workloads from PostgreSQL to a data warehouse like Amazon Redshift can pose challenges during the change data capture (CDC) phase when dealing with partitioned tables. In this post, we illustrate how we can migrate data from PostgreSQL partitioned tables to a single table on the target database using AWS Database Migration Service (AWS DMS). […]