Category: Amazon DynamoDB

In November 2020, we launched DynamoDB support for PartiQL. With PartiQL, you can codify your DynamoDB data operations using familiar SQL syntax and get the fast, consistent performance that DynamoDB customers have long depended on. In this post, we explain how DynamoDB’s PartiQL support helps new DynamoDB developers learn faster and provides existing DynamoDB developers […]

The business problem of real-time data aggregation is faced by customers in various industries like manufacturing, retail, gaming, utilities, and financial services. In a previous post, we discussed an example from the banking industry: real-time trade risk aggregation. Typically, financial institutions associate every trade that is performed on the trading floor with a risk value […]

The collection, aggregation, and reporting of large volumes of data in near real time is a challenge faced by customers from many different industries, like manufacturing, retail, gaming, utilities, and financial services. In this post, we present a serverless aggregation pipeline in AWS. We start by defining the business problem, introduce a serverless architecture for […]

Managing virtual machine images that you standardize through configuration, consistent security patching, and hardening (also called “golden images”) is a time-consuming task. System administrators and database administrators responsible for these tasks have to define the characteristics of these images (such as which software to pre-install, which versions to use, and which security configurations to apply). […]

Amazon DynamoDB transactions help developers perform all-or-nothing operations by grouping multiple actions across one or more tables. These transactions provide ACID (atomicity, consistency, isolation, durability) compliance for multi-item operations in applications. The following scenarios are common use cases for DynamoDB transactions: Financial transactions where an all-or-nothing operation is required. For example, transactions can be used […]

With the announcement of Amazon CloudWatch Metric Streams, you can now stream near-real-time metrics data to a destination such as Amazon Simple Storage Service (Amazon S3). Metric Streams supports two primary use cases: Third-party providers – You can stream metrics to partners to power dashboards, alarms, and other tools that rely on accurate and timely […]

With customers scaling up their AWS workloads across hundreds, if not thousands of AWS resources, customers have expressed the need to centrally manage and monitor their backups. They want to have a standardized way to manage their backups at scale. AWS Backup enables you to centralize and automate data protection across AWS services. AWS Backup […]

There are many scenarios in which you might need to migrate your Amazon DynamoDB tables from one AWS account to another AWS account, such as when you need to consolidate all your AWS services into centralized accounts. Consolidating DynamoDB tables into a single account can be time-consuming and complex if you have a lot of […]

Legacy application modernization can be complex. To reduce complexity and risk, you can choose an iterative approach by first replatforming the workload to Amazon Aurora. Then you can use the cloud-native integrations in Aurora to introduce other AWS services around the edges of the workload, often without changes to the application itself. This approach allows […]

A common practice when creating a data model design, especially in the relational database management system (RDMS) world, is to start by creating an entity relationship diagram (ERD). Afterwards, you normalize your data by creating a table for each entity type in your ERD design. The term normalization refers to the process of organizing the […]