AWS Glue vs. Informatica 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

I am working in a medical device company and we require a large amount of data to analyze. Handling large amounts of data using this tool is very easy and the user interface is easy and simple to navigate. Earlier we used to use excel and text files to extract the data but now using this tool we have improved in transforming the data.

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

• Improve the business process outcomes
• Create internal/external operational efficiencies
• Product functionality and performance

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

• Dependency with other systems like Hadoop as it's data repository.
• Service slow connection sometimes.
• Configuration should be easy.

Incentivized

While easy to set up and manage monitoring for large datasets, its complexity can be a barrier for new users. Integration with AWS Ecosystem, Managed Monitoring, Dashboards and monitoring tools for AWS Glue are generally easy to set up and maintain, Automated Data Pipelines. Automates data pipeline creation, making it efficient for certain data integration

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.

To improve the business process outcomes we have purchased this tool. By using this tool data preparation is easy and much [more] flexible and I would suggest [it as] a good option to try. As it is built with powerful AI and supports as large datasets as we can get without any reduction in performance.

Incentivized

• We are using GLUE for our ETL purpose. it’s ease with other our AWS services makes our ROI, 100% ROI.
• One missing piece was compatibility with other data source for which we found a work around and made our data source as S3 only, so our dependencies on other data source is also reducing

Incentivized

• Dependency on hadoop cluster as its repository

Incentivized