AWS Glue is a serverless ETL integration tool to process your data. I have used Glue Jobs(python) in my Migration project and I liked the below features of AWS Glue service.

a> Serverless ETL tools to start data integration

b> Support Python3.9 version including several popular packages like pandas, SQLalchmy, etc. So no need to explicitly include/install those packages.

c> Scheduled and an event-based job that can be used in Workflow

d> Monitor Dashboard for Active Glue Jobs Review collected by and hosted on G2.com.

if we have to use an external library like Cx_oracle or another, we have to use Python wheel files, that some time is quite confusing for developers. Review collected by and hosted on G2.com.

Comment:"AWS and AWS Glue has great capability and makes using Spark, PySpark and now even Ray easy, also AWS gives us a lot of human support to use AWS Glue. However, it is still quite complex and to set it up (with code, not GUIs) is still not super easy and needs a lot of tweaking. Also cost explode quite easily. One needs to be careful to build prototypes and experiment and tweak without not creating too much cost. A product like AWS Glue prototype job could be a great addition... it could automatically enforce best practices for prototyping on small datasets and extrapolating findings on large datasets... E.g. a Glue job assistant could ask some question about the data and the job that needs to be done and then suggest a test case and enforce it (i.e. allow only few dpus, short runtime, little data, but still allowing for extrapolating insights to large datasets). Still AWS Glue lead us to efficiently running jobs that need little to no maintainence and which run smoothly and reliably." Review collected by and hosted on G2.com.

visuals, log and debug

"select and onboarding was difficult, but overall its ok as a product for etl, design was the most hardest and time consuming part, it take a while to refine the process, but one its done right it a perfect tool, we are still working on this process right." Review collected by and hosted on G2.com.

Integration with other AWS services: AWS Glue can be integrated seamlessly with other AWS services, such as AWS Lambda, Amazon S3, AWS Step Functions, and Amazon CloudWatch, allowing users to build end-to-end data processing pipelines and workflows within the AWS ecosystem. Review collected by and hosted on G2.com.

Cost considerations - Even though AWS Glue offers a serverless architecture, the cost of running data integration jobs can still vary based on factors such as the volume of data, the complexity of transformations, and the frequency of job runs. Users need to be mindful of the costs associated with data transfer, storage, and processing and optimize their usage accordingly. Review collected by and hosted on G2.com.

Scalability: AWS Glue is a fully managed service, which means it can scale automatically based on your data processing needs. This makes it easy to handle large data volumes and perform ETL jobs efficiently.

Easy to use: AWS Glue provides a simple and user-friendly interface for building and managing ETL workflows, making it accessible even to users without prior ETL experience.

Cost-effective: AWS Glue charges on a per-second basis, which means you only pay for the time and resources you use. This makes it a cost-effective solution for small and large-scale data processing jobs. Review collected by and hosted on G2.com.

Limited customization: While AWS Glue allows users to create custom ETL scripts in Python, Scala, or Java, it has some limitations on the level of customization that can be achieved. This may limit the flexibility of the tool for some use cases.

Data privacy and security concerns: Since AWS Glue is a cloud-based service, customers need to be mindful of data privacy and security concerns. Sensitive data may need additional security measures to protect it from unauthorized access. Review collected by and hosted on G2.com.

Glue is nothing but the ETL (Extract ,Transform,Load) Tool .It is mainly data extraction and transformation and loaded as other format as physical source.Compatibility is the best and here the versions are maintained as the backup of every datacolumns updated Review collected by and hosted on G2.com.

Cost in data transfer is high, debugging challenges are there Review collected by and hosted on G2.com.

Interactive dev session. Script running feature is one of the biggest upside of this tool Review collected by and hosted on G2.com.

File organisation among team mates is really messy in the aws glue. Folder structure should be added. On top of this, without auto shutdown of session feature in interactive session, sometime it really shots up the cost. Documentation for the aws glue could have better. Review collected by and hosted on G2.com.

AWS Glue is one of the best services offered by Amazon and it's very efficient in the data transfer between different data stores, and the exchange of data for analysis. I find AWS Glue very useful in data integration for the benefits it provides, such as:

1. Easy scalability for processing high amounts of data

2. A minimal and simple user interface for the customer experience.

3. As AWS Glue is serverless, it is highly cost-efficient, as we will be paying only for the resources we use. Review collected by and hosted on G2.com.

The following are some examples of what I like about AWS Glue:

1. The users have very limited control over the infrastructure, so it restricts them from doing customizations

2. Currently it only supports Python and Scala programming languages, so this can be highly improved.

3. Integrating AWS Glue with other services out of AWS would be a little challenging. Review collected by and hosted on G2.com.

Being full managed ETL service and completely serverless architecture ,the data catalog feature to search data and vast resources of aws that can be used with glue makes it best. Review collected by and hosted on G2.com.

Limited control over architecture and very less documentation of usage. The customization is very less and it can have high cost. It needed to be trained perfectly. Review collected by and hosted on G2.com.

We can use drag and drop method to create etl jobs and user friendly tool to create our own customised etl jobs and can be integrated with cloudwatch as well and dynamodb using exact pointers and values inside the code used glue Review collected by and hosted on G2.com.

Job run is bit slow

We cannot select the large piece of code which is requied

In previous version it was only on card view now it is in list view its better to implement only card view for better understanding Review collected by and hosted on G2.com.

I like its integration and ability to handle all data-related tasks. The solution is highly user-friendly, and its features are easy to use. The new addition of AWS Glue Data Catalog is also very beneficial, making the tool even more helpful for its users. Review collected by and hosted on G2.com.

limited to working within the AWS good environment and mostly work on python and Scala. Integration with other platforms might be difficult and large datasets makes its little bit slow and less amount of small datasets for practice Review collected by and hosted on G2.com.