Data Transformation Tools In The Azure Space

James Serra gives us an overview of the major tools you would use for ETL and ELT in Azure:

If you are building a big data solution in the cloud, you will likely be landing most of the source data into a data lake.  And much of this data will need to be transformed (i.e. cleaned and joined together – the “T” in ETL).  Since the data lake is just storage (i.e. Azure Data Lake Storage Gen2 or Azure Blob Storage), you need to pick a product that will be the compute and will do the transformation of the data.  There is good news and bad news when it comes to which product to use.  The good news is there are a lot of products to choose from.  The bad news is there are a lot of products to choose from :-).  I’ll try to help your decision-making by talking briefly about most of the Azure choices and the best use cases for each when it comes to transforming data (although some of these products also do the Extract and Load part

The only surprise is the non-mention of Azure Data Lake Analytics, and there is a good conversation in the comments section explaining why.

Related Posts

Overriding Spark Dependencies

Landon Robinson shows how to override a Spark dependency located on the classpath: This doesn’t draw the line exactly where the method changed from private to public, but generally speaking:– gson-2.2.4.jar: the method is private, and therefore too old for use here– gson-2.6.1: the method is public, and works fine.– Somewhere between the two, the […]

Read More

Kafka and MirrorMaker

Renu Tewari describes what MirrorMaker does for Kafka today and what is coming with version 2: Apache Kafka has become an essential component of enterprise data pipelines and is used for tracking clickstream event data, collecting logs, gathering metrics, and being the enterprise data bus in a microservices based architectures. Kafka is essentially a highly […]

Read More

Categories

January 2019
MTWTFSS
« Dec Feb »
 123456
78910111213
14151617181920
21222324252627
28293031