Category: Customer Solutions

Amagi built a Global Metadata Store on Amazon Neptune to model billions of interconnected media metadata relationships. Learn how their RDF knowledge graph, paired with Amazon OpenSearch Service and a custom blank-node synchronization layer, delivers deep semantic queries and sub-500ms transactional reads across 2,500+ channels and 150+ countries.

How Amazon Fire TV redesigned its Continue Watching watch-progress data model on Amazon DynamoDB with vertical partitioning and hash-prefixed sort keys for parallel reads, removing item-size limits, cutting write costs by 97%, and keeping reads under 50 milliseconds at any profile size.

Learn how Intuit and AWS validated Amazon ElastiCache resilience under a real Availability Zone impairment using AWS Fault Injection Service, cutting recovery from over 50 minutes to under 2 minutes with no manual intervention and reducing customer impact to effectively zero.

How CORTO scaled Amazon Aurora PostgreSQL with pgvector to 7.6 billion vectors and 2.5 billion documents in production, delivering sub-second legal search for 10,000+ law firms at 75% lower storage cost.

Channel Corporation shares how they split their all-purpose Amazon DynamoDB User table into role-specific tables, moving Badge data into a dedicated UserBadge table to stop transaction-conflict throttling and GSI back pressure, and how they ran a zero-downtime online migration using DynamoDB Export and Import with Amazon S3 and AWS Glue.

Managing payment infrastructure at scale presents unique challenges that impact both performance and operational efficiency. In this post, we share the technical and operational challenges Nubank faced with self-managed PostgreSQL, the evaluation criteria they established for selecting database solutions, and the results from their successful migration to Amazon Aurora PostgreSQL-Compatible Edition. Nubank achieved up to 1,900x query performance improvements in specific cases.

In this post, we show how Dynata simplified database cost optimization and accelerated modernization to AWS Graviton processors by adopting Database Savings Plans. Rather than managing Reserved Instances across multiple database services, Dynata consolidated their cost commitment into a single, flexible pricing model. This reduced operational overhead by 70%, extended cost coverage to Amazon Aurora serverless, and lowered total cost of ownership as their infrastructure evolved.

In this post, you will learn how CRED built an automated orchestration framework around Amazon RDS blue/green deployments. The framework performs engine upgrades, instance scaling, storage optimization, and Change Data Capture (CDC) pipeline migration across their entire fleet. This approach achieved zero data loss incidents and zero production incidents.

In this post, we share how Securonix migrated hundreds of Amazon ElastiCache clusters from Redis OSS to Valkey, achieving a 20% reduction in caching costs. This amounts to over $100,000 in annualized savings. The migration also improved CPU utilization and overall throughput across Securonix’s global SIEM platform, which processes hundreds of terabyte data volumes daily for enterprise security teams worldwide.

Managing massive data volumes at scale presents significant operational challenges. At Similarweb we faced these challenges with Apache HBase and found a solution in Amazon DynamoDB. Similarweb is a digital intelligence platform that provides AI-powered insights into website traffic, app usage, and market trends to help businesses benchmark competitors and optimize growth strategies. We faced growing scalability and operational complexity issues with our existing Apache HBase infrastructure, which prompted us to explore more flexible and efficient alternatives. This post walks you through our journey migrating our data storage from Apache HBase to DynamoDB. We discuss the technical challenges, migration approach, data modeling strategies, cost optimization techniques, and key benefits achieved along the way.