AWS Glue Elastic Views Preview

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AWS Glue Elastic Views is now available in preview. You will need an AWS Account Number in order to request access. Please submit the information below to request an invitation to the preview. We will contact you with instructions if you are accepted.

AWS Glue Elastic Views makes it easy to combine and replicate data across multiple data stores without you having to write custom code. With AWS Glue Elastic Views, you can use familiar Structured Query Language (SQL) to quickly create a virtual table—called a view—from source data stores. Based on this view, AWS Glue Elastic Views copies data from the source data store and creates a replica—called a materialized view—in a target data store.

AWS Glue Elastic Views currently supports Amazon DynamoDB as a source data store and Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service as target data stores.

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Please provide a high level description of the business problem you would like to solve with AWS Glue Elastic Views (e.g., Our application uses Amazon DynamoDB as the operational database. We want to facilitate a full text search capability on this data by copying it over to Amazon Elasticsearch Service).

How are you solving this business problem today? (e.g., Do you have an existing data pipeline to move data from Amazon DynamoDB to Amazon Elasticsearch Service, Amazon S3, or Amazon Redshift?)

What works well and what are some of the challenges with your current solution?

What sources do you require to use with Elastic Views? [Select up to 3]

What targets do you require to use with Elastic Views? [Select up to 3]

Does your business problem require Elastic Views to join data across multiple data stores? (e.g., Our application requires to join data from an Orders table in Amazon DynamoDB with data from a Customer table in Amazon Aurora MySQL to create a real time dashboard of orders per customer.)

Does your business problem require Elastic Views to aggregate data? (e.g., Our web application stores clickstream data in DynamoDB. Our BI application requires to aggregate the number of clicks by product per hour.)

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