Category: Database

By Lenley Hensarling, Chief Product Officer – Aerospike By Akshay Patel, Senior Practice Lead, SaaS Partners – AWS SaaS Factory By Anthony McClure, Senior Partner Solutions Architect – AWS SaaS Factory By Bill Tarr, Principal Solutions Architect – AWS SaaS Factory Aerospike Real-time, high-performance workloads demand low-latency databases that can scale to meet the most […]

Wawanesa migrated their on-premises Guidewire platform to Guidewire Cloud Platform (GWCP) to enhance digital user experience and leverage cloud agility. They replicated GWCP data to AWS using Database Migration Service, maintaining existing processes while futureproofing operations. This article covers migration challenges, lessons, and outcomes.

By Andy Boutte, Principal Solutions Architect, DuploCloud       Ian Hutchinson, VP, Sales, DuploCloud       Ranjith Raman, Principal Solutions Architect, AWS SaaS Factory DuploCloud Organizations building software-as-a-service often start with a true multi-tenant model, benefiting from economies of scale that comes with sharing infrastructure resources across tenants. However, often tenants need to […]

By Israel Mendes, Data Engineering leader – Caylent By Washim Nawaz, Analytics Specialist – AWS By Isaac Owusu-Hemeng, Customer Solutions Manager – AWS By Muz Syed, Sr. Partner Solutions Architect – AWS Caylent  In this post, we will discuss how APN Premier partner Caylent leveraged a 3-Day Experience Based Acceleration (EBA) workshop to finalize and […]

This post presents a cost-effective, serverless multi-tenant SaaS architecture utilizing AWS managed services. Users can belong to multiple tenants via Amazon Cognito user groups, and the solution enables seamless tenant switching and allows tenants to define custom roles with Amazon DynamoDB transactions. By leveraging AWS services, the architecture provides security, isolation, custom permissions, and flexibility to scale without operational overhead.

In today’s industrial landscape, smart manufacturing is pivotal for sustainability and efficiency gains. However, organizations face challenges in gathering and consolidating data from multiple, often outdated sources on the manufacturing floor. LTIMindtree’s AWS-powered Digital Command Center (DCC) solution addresses this by enabling data acquisition, management, real-time KPI monitoring, and analytics-driven insights.

Learn how to connect the ThoughtSpot analytics platform to an Amazon Aurora MySQL database for real-time operational analytics. This post outlines the steps to create an Aurora MySQL instance, populate it with sample data, create a connection from ThoughtSpot, and build generative AI-powered analytics using natural language search. By integrating ThoughtSpot and Aurora MySQL, businesses can get instant insights from their transactional database.

Many enterprises still rely on the Adabas database and Natural programming language for critical workloads, facing rising license costs and a shrinking talent pool. To reduce reliance on these aging technologies and enable digital transformation, companies are modernizing to AWS with Advanced’s solutions. Advanced offers automated refactoring of Natural code to Java/C# and replatforming to execute Natural on Windows, along with migrating Adabas databases to modern relational databases.

Comprinno migrated a fitness app’s databases from Google Cloud to AWS to reduce costs. Challenges included migrating large PostgreSQL databases without downtime and accessing Google’s managed subnets. Comprinno established a VPN between clouds, used a SQL proxy to enable the AWS Database Migration Service, and parallelized data loading to meet the tight migration window. By moving to Graviton-based Amazon RDS, the customer reduced database costs by 30%.

Pinecone has developed a novel serverless vector database architecture optimized for AI workloads like retrieval-augmented generation. Built on AWS, it decouples storage and compute and enables efficient intermittent querying of large datasets. This provides elasticity, fresher data, and major cost savings over traditional architectures. Pinecone serverless removes bottlenecks to building more knowledgeable AI applications economically at scale on AWS.