AWS Glue vs. Azure Data Catalog

One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.

Incentivized

Azure Data Catalog helps us solve data discovery problems
brilliantly. Our organization created a single source of truth for our data,
which allowed us to develop BI and data science solutions. We can drag tables
or data sources to manage workflow. Some of the more complicated data normalization
or standardization issues need to be simplified, and I'd like to see that
happen.

Incentivized

• It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it.
• As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues.
• It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier.

Incentivized

• It's easy to use and implement.
• Ownership of the data.
• It's helpful for all businesses.
• Policy on data preservation.
• It can utilize various data sources.
• Data management is secure and simple.

Incentivized

• In-Stream schema registries feature people can not use this more efficiently
• in Connections feature they can add more connectors as well
• The crucial problem with AWS Glue is that it only works with AWS.

Incentivized

• Maintenance and creation of documentation for data sources takes a lot of time
• One cannot connect to data using a client's app unless they know the locus of the data source.

Incentivized

Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios.

Incentivized

AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.

Azure Data Catalogue was chosen for

• Microsoft's customer service and expertise
• Experience with Azure Cloud Solutions
• Reviews from peers on functionality and performance
• Product roadmap
• Overall costs

Incentivized

• It had a positive impact on the way we build our data lake.
• It is the single source of truth for data structure (schemas/tables/views).

Incentivized

• Azure platform makes it easier for us to register & catalogue all available information easily. This way when the customer actually made a sudden request or they want to access sensitive information on their own, the data is readily presented to them. Needless to say we use this mined and catalogue data for a variety of inhouse training and other improvement initiatives.

Incentivized