Category: Advanced (300)

In this post, we discuss a design for a highly searchable movie content graph database built on Amazon Neptune, a managed graph database service. We demonstrate how to build a list of relevant movies matching a user’s search criteria through the powerful combination of lexical, semantic, and graphical similarity methods using Neptune, Amazon OpenSearch Service, and Neptune Machine Learning. To match, we compare movies with similar text as well as similar vector embeddings. We use both sentence and graph neural network (GNN) models to build these embeddings.

AWS has partnered with InfluxData to launch Amazon Timestream for InfluxDB, a managed version of the popular InfluxDB 2.x open source time series database engine. In this post, we demonstrate how to use the AWS InfluxDB migration script to migrate your data from your existing InfluxDB OSS 2.x instances to Timestream for InfluxDB. At the end of this post, we show one way to perform a live migration, with additional AWS resources.

As customers are migrating to the AWS Cloud to take advantage of managed database services such as Amazon RDS for MySQL, Amazon RDS for MariaDB, and Amazon Aurora MySQL-Compatible Edition, they also look to automate these administrative tasks. This post shows how a DBA or other user with access to a custom API can make MySQL and MariaDB backup requests. It uses Infrastructure as Code (IaC) with the AWS CDK to simplify the deployment.

In this post, we explore how to transition from using Rockset to OpenSearch Service for your DynamoDB use-case effectively. To illustrate this integration, we consider a real-world example of a gaming company that tracks user interactions, such as in-game purchases and player scores, using DynamoDB. This data needs to be analyzed in real time to provide insights into user behavior, detect anomalies, and personalize the gaming experience.

In this post, we explore the steps to configure Oracle RAC as a source for AWS DMS.

Amazon RDS for SQL Server now supports configuring password policies for logins using SQL Server Authentication. In this post, we guide you through the process of enabling the password policy for Amazon RDS for SQL Server and creating a SQL Server login that adheres to the policy.

In this post, we demonstrate a process for migrating an Amazon QLDB ledger into Amazon Aurora PostgreSQL using the US Department of Motor Vehicles (DMV) sample ledger from the tutorial in the Amazon QLDB Developer Guide as an example. You may use this solution as a foundation for your own migration, altering it as necessary for your schema and migration strategy.

In this post, we discuss other native indexes supported in Amazon Aurora PostgreSQL-Compatible Edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL, including GIN, GiST, HASH, and BRIN, and their use cases.

In this series of posts, we discuss index types supported in Amazon Aurora PostgreSQL-Compatible edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL and their use cases. In this post, we discuss the native B-tree index and its variations.

AWS DMS provides the capability to validate your data as you migrate from various supported sources to AWS. Data integrity and accuracy is one of key requirements we often hear about from our customers that determines a successful migration project. In this post, we delve deep into AWS DMS data validation feature. We explore its benefits, configurations, and use cases.