From the course: Amazon Web Services: Data Analytics
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Summary of tools - Amazon Web Services (AWS) Tutorial
From the course: Amazon Web Services: Data Analytics
Summary of tools
- It's interesting to see how Amazon is representing their services around the data analytics architecture. You can see that what they've shown here is that there's three different layers in analytics. The first is storage, then serverless compute, then data processing. And the primary location or service for storage is not a database anymore, that's why I started this course with S3 and Athena, it's a datalike. Why? It's cheaper. It's simpler to set up. S3 itself is serverless and now we have Athena, which is serverless. Working with serverless services allows you to be much more flexible and it reduces costs. The industry is moving there fast. So in addition to S3, another serverless offering is the AWS Glue Data Catalog, which is a centralized storage location for the metadata for the files in S3. In the next layer, we have serverless compute. We have the Kinesis Firehose, we have serverless ETL with AWS Glue, we have the very new serverless data warehouse queries for archival data…
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