AWS Database Blog

Category: Database

Optimizing for cost with Amazon DocumentDB (with MongoDB compatibility)

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. You can use the same MongoDB 3.6 application code, drivers, and tools to run, manage, and scale workloads on Amazon DocumentDB without worrying about managing the underlying infrastructure. As a document database, Amazon DocumentDB […]

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Moving to the cloud: Migrating Blazegraph to Amazon Neptune

During the lifespan of a graph database application, the applications themselves tend to only have basic requirements, namely a functioning W3C standard SPARQL endpoint. However, as graph databases become embedded in critical business applications, both businesses and operations require much more. Critical business infrastructure is required not only to function, but also to be highly […]

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Introducing the Amazon Database Migration Accelerator

Today, we announce the launch of Amazon Database Migration Accelerator (DMA). Amazon DMA brings together AWS Database Migration Service (DMS), AWS Schema Conversion Tool (SCT), and AWS database migration experts to help customers migrate away from traditional commercial databases at fixed prices. At launch, we offer Amazon DMA to customers migrating from Oracle and SQL […]

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Change data capture from Neo4j to Amazon Neptune using Amazon Managed Streaming for Apache Kafka

After you perform a point-in-time data migration from Neo4j to Amazon Neptune, you may want to capture and replicate ongoing updates in real time. For more information about automating point-in-time graph data migration from Neo4j to Neptune, see Migrating a Neo4j graph database to Amazon Neptune with a fully automated utility. This post walks you […]

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Building globally distributed MySQL applications using write forwarding in Amazon Aurora Global Database

AWS released Amazon Aurora Global Database in 2018. Aurora Global Database enables two primary use cases. The first use case is supporting a disaster recovery solution that can handle a full regional failure with a low recovery point objective (RPO) and a low recovery time objective (RTO), while minimizing performance impact to the database cluster […]

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How Waves runs user queries and recommendations at scale with Amazon Neptune

This is a guest post by Pavel Vasilyev, Director of Solutions Architecture at ClearScale, an APN Premier Consulting Partner that provides a full range of cloud professional services. When executive management from Waves, a Y Combinator-backed mobile dating app, realized they were outgrowing their existing IT architecture on Google Cloud, they knew it was time […]

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Getting started with Amazon DocumentDB (with MongoDB compatibility); Part 3 – using Robo 3T

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. You can use the same MongoDB 3.6 application code, drivers, and tools to run, manage, and scale workloads on Amazon DocumentDB without having to worry about managing the underlying infrastructure. As a document database, […]

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Best practices for exporting and importing data from Amazon Aurora MySQL to Amazon S3

You can build highly distributed applications using a multitude of purpose-built databases by decoupling complex applications into smaller pieces, which allows you to choose the right database for the right job. Amazon Aurora is the preferred choice for OLTP workloads. Aurora makes it easy to set up, operate, and scale a relational database in the […]

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Scaling Amazon DocumentDB (with MongoDB compatibility), Part 1: Scaling reads

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, fully managed document database service that supports MongoDB workloads. With Amazon DocumentDB, you can run the same application code and use the same drivers and tools you use with MongoDB. This post shows you how the modern, cloud-native database architecture of Amazon DocumentDB allows […]

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Building a customer 360 knowledge repository with Amazon Neptune and Amazon Redshift

Organizations build and deploy large-scale data platforms like data lakes, data warehouses, and lakehouses to capture and analyze a holistic view of their customer’s journey. The objective of such a data platform is to understand customer behavior patterns that influence satisfaction and drive more engagement. Applications today capture each point of contact with a customer, […]

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