AWS Database Blog
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.
Optimize Amazon RDS performance with io2 Block Express storage for production workloads
Choosing the right storage configuration that meets performance requirements is a common challenge when creating and managing database instances. In this post, we provide an end-to-end guide for what storage class to choose depending on your use case. In addition, we compare the performance of different storage volumes on open source engines supported by Amazon RDS, to validate them from a database-centric perspective.
How Monzo Bank reduced cost of TTL from time series index tables in Amazon Keyspaces
At Monzo, we use Amazon Keyspaces (for Apache Cassandra) as our main operational database. Today, we store over 350 TB of data across more than 2,000 tables in Amazon Keyspaces, handling over 2,000,000 reads and 100,000 writes per second at peak. In this post, we share how we used a different mechanism for row expiry than the Time to Live setting in Amazon Keyspaces to reduce our operating costs for an index while preserving its semantics.
Migrating Oracle Databases from Exadata to Amazon RDS for Oracle: Addressing Performance Considerations
In this post, we provide a comprehensive guide for addressing performance considerations when migrating Oracle databases from Exadata to Amazon RDS for Oracle. We explore methods to analyze Exadata workload characteristics, including determining Smart IO usage, examining database-level I/O patterns, and identifying SQLs that utilize Exadata-specific features. We also discuss various alternatives available on RDS for Oracle to mitigate potential performance impacts.