Cloud ETL tools
Switchboard Sep 2
Table of Contents
Modern data analytics is rapidly moving toward cloud-based platforms. But before analytics can be performed on your data in the cloud, it must be migrated from its original source.
This means dealing with mushrooming data volumes, data silos, and increasingly complex data structures. Enter the growing field of cloud-based ETL tools.
What are Azure ETL tools?
Azure Data Factory is a cloud-based ETL tool from Microsoft, designed to help users migrate and integrate data from different sources in the Azure cloud. Using Azure Data Factory Studio, you can integrate data from both cloud-based databases and on-premises Microsoft SQL Server. Included is a service called Azure HDInsight for processing the dataset once it has been loaded.
However, Azure Data Factory is not a complete ETL tool per se, since it merely issues commands for data transformations rather than executing the commands itself. This makes Azure Data Factory more of an ETL framework, as opposed to Microsoft’s SSIS (SQL Server Integration Service) which can be used to execute the whole ETL pipeline.
Microsoft itself describes Azure Data Factory as “more of an Extract-and-Load (EL) and Transform-and-Load (TL) platform rather than a traditional Extract-Transform-and-Load (ETL) platform.“
What ETL tool is on Google cloud?
No discussion of modern cloud ETL tools would be complete without mentioning Google. As with the Microsoft ETL tools, Google offers a panoply of different software for building data pipelines, all included in the Google Cloud Platform suite. And these run on the same infrastructure that Google uses for its own public services.
Google Cloud Platform includes many different features, such as serverless hosting, NFS (Network File System) storage, a variety of database services (including SQL, NoSQL, and Cloud SQL), network traffic management, BigQuery for data analysis, and ML modeling.
Vendors have built ETL tools on top of Google’s services. These include many open-source ETL software, such as Apache Airflow, as well as proprietary tools. But the best ETL tools provide end-to-end solutions, ready to process your data pipeline.
Does AWS have an ETL tool?
Yes, it’s called AWS Glue, and it’s a managed ETL service accessed via the AWS Management Console. In AWS Glue, ETL can be performed end-to-end, including job scheduling and triggering, and metadata handling. However, the tool only supports services running on AWS, such as Amazon Aurora, Amazon Redshift, and Amazon S3, so this could limit your AWS ETL architecture.
There are also third-party AWS ETL tools that support non-AWS services. When choosing between a third-party AWS data pipeline vs Glue, it’s important to consider a number of different aspects. These include whether the tool integrates with all of your data sources, whether reliability matches that of AWS Glue, the degree of performance and scalability, how replication is handled, and the availability of technical support.
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