AWS Database Blog
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.
Monitoring your Amazon Aurora PostgreSQL-Compatible and Amazon RDS PostgreSQL from integer sequence overflow
In this post, we discuss integer sequence overflow, its causes, and—most importantly—how to efficiently set up alerts using Amazon SNS and use AWS Lambda to resolve such issues in Amazon Aurora PostgreSQL-Compatible Edition and Amazon RDS for PostgreSQL.
Implement automatic conflict detection and resolution for Oracle GoldenGate bi-directional replication between Amazon RDS for Oracle databases
In this post, we show how to implement automatic conflict detection and resolution (Auto-CDR) for Oracle GoldenGate bi-directional replication between Amazon RDS for Oracle databases.
Improve Amazon Timestream for InfluxDB security posture by automating rotation for long-lived credentials
In this post, we walk you through how to make your Amazon Timestream for InfluxDB deployments more secure by offering a mechanism to automatically rotate long-lived credentials. We use AWS Secrets Manager to store your tokens and user credentials as secrets and rotate the secrets using the included AWS Lambda functions.
Comparison of test_decoding and pglogical plugins in Amazon Aurora PostgreSQL for data migration using AWS DMS
In this post, we provide details on two PostgreSQL plugins available for use by AWS DMS. We compare these plugin options and share test results to help database administrators understand the best practices and benefits of each plugin when working on migrations.
Enhance the reliability of airlines’ mission-critical baggage handling using Amazon DynamoDB
In the world of air travel, baggage handling isn’t just about keeping track of baggage, but a seamless orchestration of different processes to improve the passenger baggage experience. A key component to make this happen is a strong database management strategy. In this post, we discuss how AWS Partner IBM Consulting developed an initiative to modernize a traditional baggage database architecture using Amazon DynamoDB and other Amazon Web Services (AWS) managed services, addressing the evolving needs of the airline industry.
Enhancing performance of Amazon RDS for Oracle with NVMe SSD hosted Smart Flash Cache and Temporary Tablespaces
In this post, we discuss temporary tablespace and Flash Cache features with local NVMe SSD-based instance storage, configuration options, typical use cases, and feature availability by engine and storage configuration. We dive deep into the tiered cache capability and how it can improve the query performance of latency-sensitive workloads. We also provide an overview of the temporary object capability.
Amazon DynamoDB re:Invent 2024 recap
For the Amazon DynamoDB team, AWS re:Invent 2024 was an incredible experience to connect and reconnect with our customers. The key themes this year were “better together” integrations, data modeling, and building globally resilient, scalable applications on DynamoDB. In case you missed some of these sessions, or you wanted to get caught up on why customers like Klarna, Krafton, Vanguard, Fidelity, and JPMorgan Chase are building on DynamoDB, you can read this helpful summary of some of the DynamoDB highlights from re:Invent 2024.
Transition from AWS DMS to zero-ETL to simplify real-time data integration with Amazon Redshift
The zero-ETL integrations for Amazon Redshift are designed to automate data movement into Amazon Redshift, eliminating the need for traditional ETL pipelines. With zero-ETL integrations, you can reduce operational overhead, lower costs, and accelerate your data-driven initiatives. This enables organizations to focus more on deriving actionable insights and less on managing the complexities of data integration. In this post, we discuss the best practices for migrating your ETL pipeline from AWS DMS to zero-ETL integrations for Amazon Redshift.