Integrate Data Across Multiple Sources with AWS Glue Elastic Views

Introduction

Data integration is a critical aspect of any data-driven organization. Today’s businesses deal with vast amounts of data from various sources, such as on-premises databases, SaaS applications, and cloud-based data warehouses. The challenge lies in bringing this data together in an accurate and efficient way.

What are AWS Glue Elastic Views?

AWS Glue Elastic Views is a fully managed service that provides a way to create, manage, and query materialized views of data that span multiple data stores. A materialized view is a precomputed table containing a query’s results. With AWS Glue Elastic Views, you can create materialized views that span multiple data sources, such as Amazon S3, Amazon RDS, and Amazon DynamoDB. This means you can easily join data from different sources and create a unified view of your data without worrying about the underlying data stores.

How Does AWS Glue Elastic Views Work?

AWS Glue Elastic Views is built on top of AWS Glue, a fully managed extract, transform, and load (ETL) service. AWS Glue Elastic Views uses the Glue Data Catalog, a metadata repository that stores information about data sources, transformations, and jobs. AWS Glue Elastic Views copies data from each source data store and creates a replica called a materialized view in a target data store. A materialized view in AWS Glue Elastic Views creates a Glue job that runs on a schedule or demand. The Glue job reads data from the specified data sources, performs the necessary transformations, and writes the results to the materialized view.

AWS Glue Elastic Views also provides a query service that allows you to query the materialized views using SQL. You can query the materialized views using any SQL client, such as AWS Athena or Amazon Redshift.

Benefits of AWS Glue Elastic Views

AWS Glue Elastic Views provides several benefits for data integration:

1. Simplifies data integration: AWS Glue Elastic Views makes integrating data from multiple sources easier. You don’t need to worry about the underlying data stores, as Glue Elastic Views handles the details.
2. Improves query performance: Materialized views are precomputed tables that can improve query performance by reducing the amount of data that needs to be processed.
3. Cost-effective: AWS Glue Elastic Views is a fully managed service, so you don’t need to worry about provisioning and managing infrastructure. You only pay for the resources used by the Glue jobs.
4. Scalable: AWS Glue Elastic Views is built on top of AWS Glue, a fully managed ETL service. This means you can easily scale up or down based on your needs.

Pricing

The pricing for AWS Glue Elastic Views is based on the number of hours the materialized view is active in a month and the amount of data processed. AWS charges $0.15 per hour for each materialized view and $0.10 per GB of data processed. There are no upfront fees or minimum commitments, and you only pay for what you use.

It’s important to note that the pricing for AWS Glue Elastic Views does not include the cost of the underlying data sources or any other AWS services that you may use, such as Amazon S3 or Amazon Redshift. You will be charged separately for these services based on their pricing models.

AWS Glue Elastic Views also offers a free tier that allows you to create and run one materialized view monthly for up to 30 minutes at no charge. This can be a great way to get started with the service and see how it can benefit your organization without incurring costs.

Conclusion

AWS Glue Elastic Views is a powerful new service that simplifies data integration across multiple sources. With AWS Glue Elastic Views, you can easily create materialized views that span different data stores and query them using SQL. This makes it easier for organizations to build and maintain their data pipelines and get insights from their data. If you’re dealing with data from multiple sources, AWS Glue Elastic Views is worth checking out.

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