AWS Glue

What differentiates AWS Glue from other similar products?

Not sure about other similar products, but found this very helpful in almost all aspects, price, compatibility, easy to use etc

What is your favorite aspect of this product?

currently working on a system to make Spark jobs configurable without writing code. Running it on Glue helps reduce the overhead of maintenance and helps it integrate with the data stored on AWS.

What do you dislike most about this product?

Database Support Limitations as It only supports structured databases.

What recommendations would you give to someone considering this product?

Include the non structured databases as well in the AWS Glue service

What differentiates AWS Glue from other similar products?

Fully Managed Service: AWS Glue is a fully managed ETL service, requiring minimal setup and infrastructure management compared to other tools, which makes it ideal for users looking to avoid complex configurations. Serverless Architecture: It automatically scales based on your data processing needs, meaning you don’t have to manage servers or worry about provisioning resources, offering high flexibility and cost efficiency. Tight Integration with AWS Ecosystem: AWS Glue integrates seamlessly with other AWS services like S3, Redshift, and Athena, providing a unified data processing and analytics solution within the AWS cloud.

What is your favorite aspect of this product?

My favorite aspect of AWS Glue is its serverless architecture, which eliminates the need for manual resource management, allowing you to focus on data processing without worrying about scaling or infrastructure.

What do you dislike most about this product?

What I dislike most about AWS Glue is its complexity in setup and configuration, especially for users who are new to the AWS ecosystem or ETL processes, which can make the learning curve steep.

What recommendations would you give to someone considering this product?

Familiarize yourself with AWS services to take full advantage of Glue’s integration with other AWS tools. Start with simple ETL jobs to get comfortable with the platform before scaling up. Utilize AWS documentation and support to help navigate the setup process and troubleshoot effectively.

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.