AWS Database Blog

Category: Database

Create an AWS DMS endpoint to a third-party account via AWS Secrets Manager integration

When configuring AWS Database Migration Service (AWS DMS) endpoints, you previously had to maintain the source and target credentials, including auditing, updating, and rotating the database credentials themselves. On December 22, 2020, we announced the integration of AWS DMS and AWS Secrets Manager, which now allows you to manage and automatically rotate the source and […]

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Building a data discovery solution with Amundsen and Amazon Neptune

This blog post was last reviewed or updated May, 2022. September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. In this post, we discuss the need for a metadata and data lineage tool and the problems it solves, how to rapidly deploy it in the language you prefer using […]

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Best practices: Redis clients and Amazon ElastiCache for Redis

In this post, we cover best practices for interacting with Amazon ElastiCache for Redis resources with commonly used open-source Redis client libraries. ElastiCache is compatible with open-source Redis. However, you may still have questions about how to optimize your applications and associated Redis client library configurations to interact with ElastiCache. These issues typically arise when […]

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Implement Oracle GoldenGate high availability in the AWS Cloud

The need to move data from one location to another in an asynchronous manner is a goal for many enterprises. Use cases might include migrating data to a reporting database, moving applications from on premises to the cloud, storing a redundant copy in another data center, configuring active/active databases across geographic locations, and performing heterogeneous […]

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Improve native backup and restore performance in Amazon RDS for SQL Server

Amazon Relational Database Service (Amazon RDS) for SQL Server makes it easy to set up, operate, and scale SQL Server deployments in the cloud. As a fully managed database service, Amazon RDS for SQL Server takes automated backups of your DB instance during the backup window. If required, you can restore your DB instance to […]

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Work with files in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL

An Oracle to Amazon Aurora PostgreSQL-Compatible Edition or Amazon Relational Database Service (Amazon RDS) for PostgreSQL migration into the AWS Cloud can be a multistage process with different technologies and skills involved, starting from the assessment stage to the cutover stage. For more information about the migration process, see Database Migration—What Do You Need to […]

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Automate the Amazon Aurora MySQL blue/green deployment process

Blue/green deployment techniques provide near zero-downtime release and rollback capabilities. This requires two identical environments that are running different versions of your application. This also extends to the underlying data layer, where you need two identical Amazon Aurora MySQL-Compatible Edition database clusters running in sync with the same dataset for seamless testing. After completing tests […]

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Introducing Graph Store Protocol support for Amazon Neptune

Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. Neptune’s database engine is optimized for storing billions of relationships and querying with millisecond latency. The W3C’s Resource Description Framework (RDF) model and the popular Labeled Property Graph model […]

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Easier and faster graph machine learning with Amazon Neptune ML

Amazon Neptune ML provides a simple workflow for training machine learning (ML) models for graph data. With version 1.0.5.0, Neptune ML delivers additional enhancements to all the steps of this workflow to reduce cost, increase speed, and offer a more flexible modeling experience. Starting with data export and data processing, Neptune ML now provides additional […]

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Get predictions for evolving graph data faster with Amazon Neptune ML

As an application developer building graph applications with Amazon Neptune, your graph data may be evolving on a regular basis, with new nodes and or new relationships between nodes being added to the graph to reflect the latest changes in your underlying business data. Amazon Neptune ML now supports incremental model predictions on graph data […]

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