Category: Database

One of the steps in migrating a database to the cloud involves transferring existing data from the source (on premises) to the target (cloud). For medium and large databases, such as those ranging from hundreds of gigabytes to 5 terabytes, speed of data transfer matters. One of the challenges is to minimize the downtime of […]

Organizations across diverse sectors are exploring novel ways to enhance user experiences by harnessing the potential of Generative AI and large language models (LLMs). In the fashion industry generative AI is revolutionizing the creative process. By analyzing user preferences and data, AI algorithms can generate unique apparel patterns and designs, bringing a new level of […]

Securing SQL Server databases in the cloud is critical, and Amazon Relational Database Service for SQL Server (Amazon RDS) provides several security features to help ensure the confidentiality, integrity, and availability of your database instances. These features include data encryption at rest and in transit, secure user authentication and authorization mechanisms, network isolation, and fine-grained […]

In addition to offering you a choice of seven well-known engines, Amazon Relational Database Service (Amazon RDS) also offers a number of deployment choices to assist you in selecting the option that best suits your workload. You can evaluate your requirements and then choose the right set of service offerings. In the latest set of […]

A knowledge graph allows us to combine data from different sources to gain a better understanding of a specific problem domain. In this post, we use Amazon Neptune (a managed graph database service) to create a knowledge graph about technology products. In addition to the data we already have in the graph, we add the […]

While databases are used to store and retrieve data, there are situations where applications should archive or purge the data to reduce storage costs or improve performance. However, there are often business requirements where an application must query both active data and archived data simultaneously. Developers need a solution that lets them benefit from using […]

Amazon DynamoDB allows you to store JSON objects into attributes and perform many operations on these objects, including filtering, updating, and deleting. This is a very powerful capability because it allows applications to store objects (JSON data, arrays) directly into DynamoDB tables, and still retain the ability to use nested attributes within these objects in […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Amazon Timestream is a fast, serverless, and secure time series database and analytics service that can scale to process trillions of time series events per day. Organizations […]

Many customers deploy the Oracle Database to an on-premises data centers running general purpose hardware or a highly customized Oracle Exadata hardware. These Oracle database customers are now looking to migrate to Amazon Relational Database Service (Amazon RDS) for Oracle, which is a fully managed commercial database that makes it easy to set up, operate, […]

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB charges for reading, writing, and storage of your DynamoDB tables, along with any optional features you choose to enable. When you create a DynamoDB table, you choose from two capacity modes that have different billing options […]