AWS Database Blog

July 2023: This post was reviewed for accuracy. An Oracle to PostgreSQL migration in 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 Know Before You Start? […]

Knowledge graph applications are one of the most popular graph use cases being built on Amazon Neptune today. Knowledge graphs consolidate and integrate an organization’s information into a single location by relating data stored from structured systems (e.g., e-commerce, sales records, CRM systems) and unstructured systems (e.g., text documents, email, news articles) together in a […]

February 2023: This post was updated for accuracy.  Please note that PostgreSQL 14 changes the default value for password_encryption to scram-sha-256. Therefore, after you upgrade from an earlier version to PostgreSQL 14, when you change a user password, the new password will use SCRAM encryption and your client libraries will need to support SCRAM in […]

Many Amazon Neptune connected data applications for knowledge graphs, identity graphs, and fraud graphs use AWS Lambda functions to query Neptune. This post provides general connection management, error handling, and workload balancing guidance for using any of the popular Gremlin drivers and language variants to connect to Neptune from a Lambda function. The connection management […]

Amazon DynamoDB is a non-relational database that delivers reliable performance at any scale. It’s a fully managed, multi-Region, multi-active database that provides consistent single-digit millisecond latency and offers built-in security, backup and restore, and in-memory caching. DynamoDB offers a serverless and event-driven architecture, which enables you to use other AWS services to extend DynamoDB capability. […]

Amazon DynamoDB is a fully managed, multi-Region, multi-active database that delivers reliable performance at any scale. Because of the flexible DynamoDB data model, enterprise-ready features, and industry-leading service level agreement, customers are increasingly moving sensitive workloads to DynamoDB. Regulated industries (e.g., education, media, finance, and healthcare) may require detailed information about data access activity to […]

Amazon Relational Database Service (Amazon RDS) and Amazon Aurora support a multitude of instance types for you to scale your database workloads based on your needs (see Amazon RDS DB instance classes and Aurora DB instance classes, respectively). In 2020, AWS announced Amazon M6g and R6g instance types for Amazon RDS and recently announced the […]

You may have stringent regulatory compliance obligations that require an effective multi-Region disaster recovery (DR) plan to mitigate a Region-wide disaster. AWS offers multiple methods to meet these needs, taking into consideration different factors such as recovery time objective (RTO), recovery point objective (RPO), and costs. In this post, I focus on how to keep […]

January 2023: Please refer to Accelerate Amazon DynamoDB data access in AWS Glue jobs using the new AWS Glue DynamoDB Export connector  for more recent updates on using Amazon Glue to extract data from Amazon DynamoDB. Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It’s a fully […]

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, […]