AWS Glue Reviews

We are using it for file ingestion. Its primary role is to ingest a file from a vendor to a database.

Its user interface is quite good. You just need to choose some options to create a job in AWS Glue. 

The code-generation feature is also useful. If you don't want to customize it and simply want to read a file and store the data in the database, it can generate the code for you.

Currently, it supports only two languages in the background: Python and Scala. From our customization point of view, it would be helpful if it can also support Java in the background.

I have been using AWS Glue for three months. We have just started using these services.

We have not been using AWS Glue for a long time. Till now, we haven't found any issues.

Their technical support is good. We faced an issue with AWS Glue where we had to read a flat file. In a flat file, you only have spaces. You don't have commas or anything else. AWS Glue does not directly support flat files. You need to provide it with an expression to read the file, and that expression itself has some limitation of characters. We contacted the AWS support team. They had a call with us and first tried to understand our problem and then our use case. We gave them some sample files for our use case, and they come up with a solution for this limitation. There are some custom patterns in AWS Glue that can be used. Even though they took some time, they provided the solution. If you give a file today, they will take three to four days to get back.

It was straightforward. A lot of documentation is available on the AWS website, which can guide you through the simple steps to set it up. Its setup was easy for me.

It is not expensive. AWS Glue works on the serverless architecture. We get charged for the time the server is up. For our use case, we have to use it once in a day, and it is not expensive for us.

We have just recently started to use this solution. We haven't used all features properly. It is good for the features we are using. We did not find any drawbacks or limitations so far. We are already getting whatever we want from it. 

I would rate AWS Glue a seven out of ten. It needs improvements in terms of Java support and the turnaround time for our problems. 

The key role of Glue is that it hosts our metadata before rolling out our actual data. This is the major advantage of using this solution and our clients client have been very satisfied with it.

The most valuable aspect of this solution is its automation and ability to sync data from the source to the solution phase. 

The technical support for this solution could be improved. In future, we would like to connect more services like Athena or Kinesis to help control more loads of data.

I have been using this solution for three years. 

This is a stable solution. We have isolated the environment using containerization so that if anything goes wrong, we have higher levels of scalability and availability. To achieve this, we have configured multiple servers for testing, UAT and development.

This is a scalable solution which is supported in our organization by Docker and Kubernetes. We have 2,000 users.

We used a vendor with an internal IT team who provided us with architecture so that we could leverage those services and reach a solution. They have 50 people in the IT team, who continuously help us and monitor the things that we are working on.

Positive

The initial setup was straightforward and took approximately one month. For deployment, we worked in two teams. One person handled all the scripting which we are developing for automation. Two other members handled the database and servers.

This solution is affordable and there is an option to pay for the solution based on your usage. 

I would rate this solution a seven out of ten. 

AWS Glue is a versatile tool and we mostly use it for "lift and shift" server migrations.

I appreciate AWS Glue for its cost-effectiveness. The service provides a good balance between its capabilities and the cost associated with using it.

In terms of improvement, the performance of AWS Glue could be faster.

I have been using AWS Glue for five years.

It is a stable product.

It is fairly scalable.

The partner program support is very good.

The initial setup is not too complex. To deploy and maintain a data platform, a general data team of around four to five skilled individuals is typically required.

For AWS Glue, there is no separate license fee. It is part of the AWS service, and you pay for its usage as part of your overall AWS bill.

Overall, I would rate AWS Glue as an eight out of ten.

I mainly use AWS Glue for ETL purposes and batch processing of data.

AWS Glue's most valuable features are the data catalog, including crawlers and tables, and Glue Studio, which means you don't have to use custom code.

There are a couple of issues with AWS Glue. First, AWS Control randomly logs off, which disturbs coding. Second, if there's a cluster-related configuration, we have to make worker notes, which is quite a headache when processing a large amount of data. In the next release, AWS Glue should include more transformations with AWS Studio.

I've been using AWS Glue for around eight months.

AWS Glue is stable.

AWS' technical support responds within an hour on email.

The initial setup was very easy, with only some minimal configuration. However, there is a drawback that once we file the name of a user, it can't be changed.

AWS Glue is quite costly, especially for small organizations. The licensing fee is around $200 per year.

Glue supports Spark, so if you have a team that's good with Spark, definitely go with Glue. I would rate AWS Glue as eight out of ten.

I use AWS Glue primarily for ETL jobs. In my organization, it's just me using it as we are a small company. The IT team consists of four people, and I am the data engineering specialist.

The best thing about AWS Glue is its scalability and how easy it is to process a large amount of data. It integrates well with Redshift, S3, and AWS Glue catalog. 

For processing extensive data, having a managed Spark service fulfills that role. If you're already working on AWS and you need to process a lot of data that can't be handled on a single node or server, AWS Glue will serve you well. While it's quite expensive, it's valuable for large data processing needs.

Setting up pipelines is challenging, especially with version control and testing requirements. While the initial setup is easy, it doesn't accommodate more complex development needs. You might feel hesitant about changing pipelines that are already running and processing business-critical data due to limited versioning and testing capabilities.

I've been using AWS Glue since 2022, so for two years.

The stability of AWS Glue is fine. I haven't had any problems with it.

The scalability of AWS Glue is commendable.

Previously, in different jobs, I have worked with Databricks for ETL processes. I've also utilized Lambda functions for handling smaller data. I didn’t switch to AWS Glue, but used it in a different context.

The initial setup of AWS Glue is easy, yet not adequate for more complex requirements. If you need to do something robust, like creating a notebook, it is straightforward. 

However, when dealing with complex pipelines handling critical business data, it's hard to set up versioning and testing.

AWS Glue receives a hesitant five out of ten from me. I recommend it if you're already on AWS and need to process large data sets. However, for smaller data volumes, I would suggest Airflow because AWS Glue can be quite expensive.