AWS Glue

What differentiates AWS Glue from other similar products?

Since it is within the AWS ecosystem, it becomes very easy to connect to other AWS systems like S3, Redshift, and Snowflake. Data crawling from S3 buckets is real-time making the database up to date and reflecting the changes done in SAP, Infor which are integrated into Data Lake through Glue. Current alternates in the market like Talend are not very robust, it is very difficult to troubleshoot complex workflows, and you need skilled manpower, Glue is built in Apache Spark which is pretty common and it's easy to develop.

What is your favorite aspect of this product?

It is a superhouse of solutions with data crawling, database management, and data cataloging it is a one-stop solution for any Data Lake Management and also makes the creation of a Data Table easy. with Python scripts It has a multi-method approach so within the system, it allows ELT or batch processing. You can also put sequential scheduling for the jobs so it can be fully automated and can run multiple jobs without an intervention.

What do you dislike most about this product?

It's not a dislike but more like the ETL is limited to Python or Scala so an advanced Python engineer is required

What recommendations would you give to someone considering this product?

If you have tables in Redshift & Snowflake must try option is Glue and since its use based costing so you can control how much you spend. Look for advanced Python scripters for creating jobs.

What differentiates AWS Glue from other similar products?

AWS Glue operates on a serverless model, meaning users don’t have to manage infrastructure. This allows for automatic scaling, which helps reduce costs and streamline operations, especially during variable workloads and provides seamlessly integrates with other AWS services such as S3, Redshift, RDS, and Athena and includes a central metadata repository known as the AWS Glue Data Catalog, which automatically discovers and organizes data.

What is your favorite aspect of this product?

One of the most appealing features of AWS Glue is its serverless nature. Users don’t need to manage any infrastructure, allowing teams to focus on developing their data workflows rather than handling server configurations and scaling issues and provides a user-friendly interface with a visual workflow editor, enabling users to create ETL jobs without extensive coding knowledge and it can handle large volumes of data and scale automatically as needed. This flexibility is essential for businesses experiencing growth.

What do you dislike most about this product?

AWS Glue can have a steep learning curve, especially for users unfamiliar with AWS services and Debugging jobs in AWS Glue can be challenging. The error messages are not always intuitive

What recommendations would you give to someone considering this product?

AWS Glue works exceptionally well with other AWS services like S3, Redshift, RDS, and Athena. If your organization is already using AWS, Glue can streamline your data workflows and provide a cohesive environment for data management and designed to handle large volumes of data, making it suitable for enterprises that require scalability and provides powerful, it may have a learning curve, especially for users unfamiliar with AWS services. Proper training and exploration of documentation are essential to leverage its full potential.

What differentiates AWS Glue from other similar products?

Cost effective and well architectural framework for efficient data pipeline.

What is your favorite aspect of this product?

Support for data stored across different Amazon RDS

What do you dislike most about this product?

Workflow customisation and data engineering needs improvement

What recommendations would you give to someone considering this product?

Has to be good in data engineering expertise