AWS Database Blog

How Omnissa saved millions by migrating to Amazon RDS and Amazon EC2

Omnissa is a digital workspace technology leader that delivers smart, seamless, and secure digital work experiences for organizations worldwide. It serves 26,000 customers, including the top seven of the Fortune 500 companies. In this post, we walk through the Omnissa’s journey of migrating its mission-critical UEM platform and self-managed SQL Server workloads from VMware Cloud on AWS (VMC-A) to Amazon RDS for SQL Server and its application servers to Amazon EC2.

How Zepto scales to millions of orders per day using Amazon DynamoDB

In this post, we describe how Zepto transformed its data infrastructure from a centralized relational database to a distributed system for select use cases. We discuss the challenges encountered with Zepto’s original architecture to support the business scale, the shift towards using key-value storage for cases where eventual consistency was acceptable, and Zepto’s adoption of Amazon DynamoDB.

Using SSL for in-transit encryption to connect Oracle as a source for AWS DMS

This post demonstrates how to implement SSL encryption for in-transit data protection when connecting Oracle Real Application Clusters (Oracle RAC) as a source to AWS Database Migration Service (AWS DMS). Additionally, it covers the unique steps required to configure SSL for Oracle Automatic Storage Management (Oracle ASM) instances.

AI-powered tuning tools for Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL databases: PI Reporter

In this post, we explore an artificial intelligence and machine learning (AI/ML)-powered database monitoring tool for PostgreSQL, using a self-managed or managed database service such as Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL.

Migrate Oracle reference partitioned tables to Amazon RDS or Aurora PostgreSQL with AWS DMS

Database migrations from Oracle to PostgreSQL are becoming increasingly common as organizations seek to optimize database costs while leveraging the benefits of open-source database solutions. However, these migrations present specific challenges, particularly when dealing with an Oracle-specific feature such as reference partitioning, which doesn’t have a direct equivalent in PostgreSQL. In this post, we show you how to migrate Oracle reference-partitioned tables to Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL-Compatible Edition using AWS DMS.

Optimize and troubleshoot database performance in Amazon Aurora PostgreSQL by analyzing execution plans using CloudWatch Database Insights

In this post, we demonstrate how you can use Amazon CloudWatch Database Insights to analyze your SQL execution plan to troubleshoot and optimize your SQL query performance in an Aurora PostgreSQL cluster.

GroundTruth reduces costs by 45% and improves reliability migrating from Aerospike to Amazon ElastiCache for Valkey

GroundTruth, an advertising platform leading the way in location- and behavior-based marketing, empowers brands to connect with consumers through real-world behavioral data to drive real business results. As our advertising platform scaled to process increased volume of ad requests and third-party segment ingestion, maintaining our Aerospike-based caching infrastructure introduced significant operational complexity and rising costs, while also compromising performance and limiting our ability to scale efficiently. To meet our requirements we implemented Amazon ElastiCache for Valkey, which streamlined our operations, improved reliability, and reduced costs. In this post, we walk through our migration journey, covering the migration strategy we adopted, the optimizations we made to reduce cost by 45%, reliability improvements including reducing write failures by 20x, and operational gains from managed service capabilities.

JSON database solutions in AWS: Amazon DocumentDB (with MongoDB compatibility)

JSON has become the standard data exchange protocol in modern applications. Its human-readable format, hierarchical structure, and schema flexibility make it ideal for representing complex, evolving data models. As applications grow more sophisticated, traditional relational databases often struggle with several challenges: Rigid schemas that resist frequent changes Complex joins for hierarchical data Performance bottlenecks when […]