AWS Database Blog

Category: Advanced (300)

Create a 360-degree master data management patient view solution using Amazon Neptune and generative AI

In this post, we explore how you can achieve a patient 360-degree view using Amazon Neptune and generative AI, and use it to strengthen your organization’s research and breakthroughs. By consolidating information from multiple sources such as electronic health records (EHRs), lab reports, prescriptions, and medical histories into a single location, healthcare providers can gain a better understanding of a patient’s health.

Oracle Application Express for Amazon RDS for Oracle demystified

Oracle Application Express (APEX) allows you to quickly develop and deploy compelling applications that solve real problems and provide immediate value. In this post, we cover the steps for installing, configuring, and upgrading an APEX repository in Amazon RDS for Oracle and ORDS. We also show how to handle APEX when performing snapshot restore or point-in-time recovery (PITR).

Use Amazon Neptune Analytics to analyze relationships in your data faster, Part 2: Enhancing fraud detection with Parquet and CSV import and export

In this two-part series, we show how you can import and export using Parquet and CSV to quickly gather insights from your existing graph data. In Part 1, we introduced the import and export functionalities, and walked you through how to quickly get started with them. In this post, we show how you can use the new data mobility improvements in Neptune Analytics to enhance fraud detection.

Monitor server-side latency for Amazon ElastiCache for Valkey

Modern applications are built as a group of microservices, and the latency for one component can impact the performance of the entire system. Monitoring latency is critical for maintaining optimal performance, enhancing user experience, and maintaining system reliability. In this post, we explore ways to monitor latency, detect anomalies, and troubleshoot high-latency issues effectively for your self-designed (node-based) ElastiCache clusters.

Monitor server-side latency for Amazon MemoryDB for Valkey

Amazon MemoryDB is a Valkey– and Redis OSS-compatible, durable, in-memory database service that delivers ultra-fast performance. With MemoryDB, data is stored in memory with Multi-AZ durability, which enables you to achieve microsecond read and single-digit millisecond write latency and high throughput. MemoryDB is often used for building durable microservices and latency-sensitive database workloads such as […]

JSON serialization using Serde Rust crates in Amazon RDS for PostgreSQL

In this post, we showcase how to use PGRX and PL/Rust to efficiently access and manipulate all built-in PostgreSQL data types in Rust. We demonstrate how to write performant functions that create and serialize JSON objects that include these built-in types. These functions are directly usable in your database and use the newly supported serde and serde_json crates. We also walk through deploying an Amazon RDS for PostgreSQL instance with PL/Rust enabled, and how PGRX type mapping allows you to use all built-in PostgreSQL types in a JSON object.

Migrate spatial columns from Oracle to Amazon Aurora PostgreSQL or Amazon RDS for PostgreSQL using AWS DMS

In this post, we discuss configurations in AWS DMS endpoints and AWS DMS tasks to migrate spatial columns from Oracle to Aurora PostgreSQL-Compatible efficiently.

Querying and writing to MySQL and MariaDB from Amazon Aurora and Amazon RDS for PostgreSQL using the mysql_fdw extension, Part 2: Handling foreign objects

In this post, we focus on working with the features of mysql_fdw PostgreSQL extension on Amazon RDS for PostgreSQL to help manage a large set of data that on an external database scenarios. It enables you to interact with your MySQL database for importing individual/large/selectively number of objects at the schema level and simplifying how we get information about the MySQL/MariaDB schema, to make it easier to ultimately read/write data. We will also provide an introduction to understand query performance on foreign tables.

Dynamic data masking in Amazon RDS for PostgreSQL, Amazon Aurora PostgreSQL, and Babelfish for Aurora PostgreSQL

There are a variety of different techniques available to support data masking in databases, each with their trade-offs. In this post, we explore dynamic data masking, a technique that returns anonymized data from a query without modifying the underlying data. In this post, we discuss a dynamic data masking technique based on dynamic masking views. These views mask personally identifiable information (PII) columns for unauthorized users. This post discusses how to implement this technique in Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL including Babelfish for Aurora PostgreSQL.