As expected. Andy Jassys announcements made during his keynote as he opened re:Invent 2020 came with lots of new announcements, some were new services and some were added features and developments to existing services.

In this video, I want to talk about AWS Glue Elastic Views, which follows on as a feature of the existing AWS Glue service which as you may know, makes it simple and cost-effective to categorize your data, clean it, enrich it and move it reliably between various data sources.

If you want to learn more about AWS Glue, then you can see our existing course content here.

At the time of announcing AWS Glue Elastic Views, it is available in Preview in a limited number of regions, meaning you have to register to be one of the first to use the service before it becomes generally available. To register, simply follow this link.

What problem does it solve? Sometimes developers will have a need to collate, combine, restructure, and replicate data from multiple different data stores within AWS. This is often achieved by writing their own custom code or using 3rd party ETL tools to manipulate the data as required in this way, however, this can come at a considerable operational, development, and management cost where the developers can be spending weeks or even months at a time deploying such a mechanism. With AWS Glue Elastic Views, this time, effort, and resource can be reduced to just minutes! So this service will play a key role in the world of Data Analytics and it’s just another example of how AWS listens to its customers and their needs to implement a service to help optimize the effectiveness of their business processes.

What is AWS Glue Elastic Views? It's a new serverless service which allows you to easily combine and replicate source data across multiple different target data stores, while at the same time, manifesting a virtual table of combined data which can then be accessed by your applications. This can all be achieved without having to write any of your own custom code. This virtual table, giving a materialized view from across your different target data stores, can be easily created using standard SQL.

Being a serverless service, you don’t have to manage any infrastructure, and it scales automatically, so from an implementation point of view, the effort and management of the service is kept to a minimum.

At the time of the announcement, AWS Glue Elastic Views supports the following:

Amazon DynamoDB
Amazon Redshift
Amazon S3
Amazon ElasticSearch

Over the coming weeks and months this list will certainly extend to many more, such as Amazon RDS and Amazon Aurora, so always check the latest AWS documentation for the most recently supported list of services.

One of the many benefits of this service is that it automatically monitors and checks for any updates made to your source data store, so that it can be replicated to your target data store, this means that any applications using AWS Glue Elastic Views will always have the latest data available at hand.

So in a nutshell, this new feature will be a welcomed addition to many organizations when it becomes generally available. They will be able to save considerable time and effort when working with their data sets to extrapolate data from different data stores allowing the creation of materialized views of data across virtual tables.

AWS re:Invent 2020 - AWS Glue Elastic Views

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