AWS Big Data

APRIL 10, 2024

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

Data Warehouse 91

Data Warehouse Analytics Metrics Snapshot 91

AWS Big Data

APRIL 3, 2024

The AWS Glue crawler generates and updates Iceberg table metadata and stores it in AWS Glue Data Catalog for existing Iceberg tables on an S3 data lake. Snowflake integrates with AWS Glue Data Catalog to retrieve the snapshot location. Snowflake can query across Iceberg and Snowflake table formats.

Data Lake 94

Data Lake Snapshot Metadata Data Architecture 94

AWS Big Data

JUNE 28, 2023

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse.

Data Warehouse 83

Data Warehouse Analytics Metrics Dashboards 83

AWS Big Data

MARCH 21, 2024

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. ETL and ELT pipelines can be expensive to build and complex to manage.

Data Warehouse 86

Data Warehouse Metrics Statistics Optimization 86