Category: Advanced (300)

Organizations require systems and mechanisms in place to gather and analyze large amounts of data as it is created, in order to get insights and respond in real time. Stream processing data technologies enable organizations to ingest data as it is created, process it, and analyze it as soon as it is accessible. In this […]

This post was co-written with Rajesh Saluja, Principal Engineer at Intuit. Intuit is the global financial technology environment that powers prosperity for 100 million consumer and small business customers with TurboTax, Credit Karma, QuickBooks, and Mailchimp. Intuit has built on AWS since 2013 and has taken an “all-in” approach in its move to the cloud. […]

Amazon DynamoDB offers high scalability and performance for applications with varying workloads. While DynamoDB excels at efficiently distributing data across multiple partitions, it inherently follows a specific sorting order based on the schema selected. In this post, we show two example data models, one designed to store e-commerce order information and one to store game […]

In this post, we demonstrate how to build a mechanism to automate the detection of sensitive data, in particular personally identifiable information (PII), in your relational database. PII is information connected to an individual and can be used to identify them. Handling PII data in a relational database, such as Amazon Aurora, requires planning and […]

The typical migration process for an Oracle database to Amazon Aurora PostgreSQL-Compatible Edition or Amazon Relational Database Service (Amazon RDS) for PostgreSQL requires both automated and manual procedures. The AWS Schema Conversion Tool (AWS SCT) can handle the automated duties of schema conversion. For specific database objects that can’t be automatically migrated, the manual duties […]

This is the first post of a two-part series. In this post, we discuss how to migrate SQL Server indexed views to materialized views in Amazon Aurora PostgreSQL-Compatible Edition or Amazon Relational Database Service (Amazon RDS) for PostgreSQL. The second post in this series will walk you through the migration of SQL Server indexed views […]

PostgreSQL is considered one of the top database choices when customers migrate from commercial databases such as Oracle or SQL Server. AWS provides two managed PostgreSQL options: Amazon Relational Database Service (Amazon RDS) for PostgreSQL and Amazon Aurora PostgreSQL-Compatible Edition. Moving from Oracle to Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL-Compatible Edition can require […]

Customers use semi-structured or unstructured data storage for various business use cases, which is schema-less and flexible in nature. One such type of semi-structured data is JavaScript Object Notation (JSON). JSON stores data in the form of KEY, VALUE, LIST, and ARRAY formats. Oracle Database stores JSON object data in CLOB data type columns. PostgreSQL […]

With the evolution of microservice-based architectures, organizations are increasingly adopting purpose-built databases. Occasionally, businesses need guidance on which cloud service and solutions are best for them, as well as a plan for helping with the migration. When performing heterogeneous database migrations, you might encounter problems with attribute patterns on NoSQL compared to traditional relational database […]

Most migrations from on-premises Oracle to Amazon Relational Database Service (Amazon RDS) for Oracle use EXPDP/IMPDB or Transportable Tablespaces using RMAN. Depending on the size and complexity, migrations are often split at the schema level and table level. In this post, we present a solution to help you identify missing schema objects in the target […]