AWS Database Blog

Over the last several years, the growth of Machine Learning (ML) has changed the paradigm of how a business operates at its core, forcing the conversation of how to tightly integrate ML into critical decision points for a user. ML can help businesses by improving customer interactions, boosting sales, and improving operating efficiency. This can […]

A common use case for Amazon RDS Custom for SQL Server is to offload the undifferentiated heavy lifting of managing the underlying infrastructure of the cluster when running SQL Server Analysis Services (SSAS). SSAS is an analytical data engine, based on the VertiPaq technology which is used in decision support and business analytics.In this post, we explain how to launch and setup Amazon RDS Custom for SQL Server and enable SSAS to run either Tabular or Multi-Dimensional model modes.

Customers often ask us how they can create an RDS Custom for SQL Server database in their existing networking infrastructure. They want to ensure that the database servers are created within the security perimeter designed by their networking teams. They also want to understand different components and services involved when creating an RDS Custom for SQL Server instance. In this post, we demonstrate how to create an RDS Custom for SQL Server instance. We also show how to create the required prerequisites within an existing networking infrastructure. Amazon RDS Custom requires these prerequisites to create the necessary resources in your AWS account.

If you’re using Amazon DynamoDB tables with provisioned capacity, one challenge you might face is how best to handle a sudden request traffic increase (spike) without being throttled. The more sudden and extended the traffic spike, the more likely a table will experience throttles. However, throttles aren’t inevitable even for spiky traffic. Here we walk you through eight designs to handle traffic spikes, and present their advantages and disadvantages.

In this post, we explain how to migrate the logins, database roles, users, and object-level permissions from on-prem or Amazon Elastic Compute Cloud (Amazon EC2) for SQL Server to Amazon Relational Database Service (Amazon RDS) for SQL Server using the T-SQL.

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports X2iedn powered by third-generation Intel Xeon Scalable processors built on the AWS Nitro System and featuring the third-generation Intel Xeon Scalable (Ice Lake) processors. SQL Server workloads are highly dependent on memory. As a result, memory-optimized Amazon Elastic Compute Cloud (Amazon EC2) instances are most commonly used by customers.

In this post, we discuss how to perform aggregations on a DynamoDB table using Amazon DynamoDB Streams and AWS Lambda. The content includes a reference architecture, a step-by-step guide on enabling DynamoDB Streams for a table, sample code for implementing the solution within a scenario, and an accompanying AWS CloudFormation template for easy deployment and testing.

In this post, we show you how you can use the RMAN XTTS functionality to migrate from an Oracle database hosted on Amazon Elastic Compute CLoud (Amazon EC2) to Amazon RDS for Oracle. Combined with Amazon Elastic File System (Amazon EFS) integration, XTTS can help reduce the complexity of your migration strategy, reduce the number and copies of data and backups required (as well as associated storage space consumption), and reduce the application downtime associated with completing the migration of your data.

In this post, we discuss an automotive manufacturing information management use case where we store information about components within a vehicle as well as the hierarchy between each of the components. For our automotive use case, we use Amazon DynamoDB to deliver transactional queries, such as component attribute lookups. We will also show you how to use DynamoDB for larger responses such as a recursive query for all the components in a vehicle. While recursive object relationships can be represented in graph databases and possibly traditional RDBMS (with complex joins), these deeper queries can also be represented in DynamoDB.

In this post, we demonstrate how to use the DBMS_CLOUD package to transfer files between S3 buckets and directories in an RDS Custom for Oracle database. We also show how you can access data from Amazon S3 directly using Oracle features such as external tables and hybrid partition tables. The features provided by DBMS_CLOUD could vary between different Oracle releases, so pay close attention to the steps in the post and make sure you reference DBMS_CLOUD in the Oracle Database 19c documentation. To avoid confusion, the option discussed in this post is for RDS Custom for Oracle, not for RDS for Oracle. RDS for Oracle offers S3 integration.