AWS Database Blog

Performing analytics on Amazon Managed Blockchain

Managed Blockchain follows an event-driven architecture. We can open up a wide range of analytic approaches by streaming events to Amazon Kinesis. For instance, we could analyze events in near-real time with Kinesis Data Analytics, perform petabyte scale data warehousing with Amazon RedShift, or use the Hadoop ecosystem with Amazon EMR. This allows us to use the right approach for every blockchain analytics use case.
In this post, we show you one approach that uses Amazon Kinesis Data Firehose to capture, monitor, and aggregate events into a dataset, and analyze it with Amazon Athena using standard SQL.

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Populating your graph in Amazon Neptune from a relational database using AWS Database Migration Service (DMS) – Part 4: Putting it all together

In this four-part series, we cover how to translate a relational data model to a graph data model using a small dataset containing airports and the air routes that connect them. Part one discussed the source data model and the motivation for moving to a graph model. Part two explored mapping our relational data model to a labeled property graph model. Part three covered the Resource Description Framework (RDF) data model. In this final post, we show how to use AWS DMS to copy data from our relational database to Neptune for both graph data models. You may wish to refer to the first three posts to review the source and target data models.

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Populating your graph in Amazon Neptune from a relational database using AWS Database Migration Service (DMS) – Part 3: Designing the RDF Model

In this four-part series, we cover how to translate a relational data model to a graph data model using a small dataset containing airports and the air routes that connect them. Part one discussed the source data model and the motivation for moving to a graph model. Part two covered designing the property graph model. In this post, we explore mapping our relational data model to a Resource Description Framework (RDF) model. You may wish to refer to parts one and two of the series to review the model. In part four, we show how to use AWS DMS to copy data from a relational database to Neptune for both graph data models.

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Populating your graph in Amazon Neptune from a relational database using AWS Database Migration Service (DMS) – Part 2: Designing the property graph model

In this four-part series, we cover how to translate a relational data model to a graph data model using a small dataset containing airports and the air routes that connect them. Part one discussed the source data model and the motivation for moving to a graph model. In this post, we explore mapping our relational data model to a labeled property graph model. You may wish to refer to part one of the series to review the source relational data model. Part three covers the Resource Description Framework (RDF) data model. In part four, we show how to use AWS DMS to copy data from a relational database to Neptune for both graph data models.

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Populating your graph in Amazon Neptune from a relational database using AWS Database Migration Service (DMS) – Part 1: Setting the stage

In this four-part series, we cover how to translate a relational data model to a graph data model using a small dataset containing airports and the air routes that connect them. Part one discusses the source data model and the motivation for moving to a graph model. We discuss this for the labeled property graph in part two and for the Resource Description Framework (RDF) data model in part three. In part four, we show how to use AWS DMS to copy data from a relational database to Neptune for both graph data models.

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Migrating your SQL Server database to Amazon RDS for SQL Server using AWS DMS

This post provides a solution for migrating your on-premises SQL Server database to Amazon RDS for SQL Server using the SQL Server backup and restore method in conjunction with AWS Database Migration Service (AWS DMS) to minimize downtime. This method is useful when you have to migrate the database code objects, including views, stored procedures, and functions, as part of the database migration.

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Introducing Amazon ElastiCache support for AWS Outposts

AWS Outposts is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to virtually any data center, co-location space, or on-premises facility for a truly consistent hybrid experience. It’s designed to meet the needs of customers who have workloads with low latency, local data processing, or data residency requirements. The Outposts […]

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AWS Database Migration Service: Obsessed with helping customers break free from old-guard databases

It is no secret that for decades enterprise customers have had troubled relationships with their old-guard database vendors. The pattern is the same: those databases are expensive, proprietary, designed for lock-in, and come with punitive licensing terms. That’s why so many customers have accelerated their migration to AWS Cloud databases. They want the benefits of […]

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Automating database migration monitoring with AWS DMS

AWS Database Migration Service (AWS DMS) is a cloud service that makes it easy to migrate relational databases, data warehouses, NoSQL databases, and other types of data stores. During data migration with AWS DMS, it’s important to monitor the status of the ongoing replication tasks, which you can do on the task’s control table and with Amazon CloudWatch.

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