AWS Glue Reviews

I have been working as a data engineer, where dealing with the ETL process is essential. We are using AWS Glue as a primary ETL tool to serve our organization's needs. I have implemented several Glue jobs still in production.

AWS Glue has enabled us to perform ETL processes efficiently, with ease of use for AWS cloud users, providing a serverless service that eliminates the need for infrastructure maintenance.

The two features I find most valuable in AWS Glue are its user interface and ease of use. The user interface is intuitive, and navigating through the Glue console is seamless. 

Additionally, its ability to integrate with other AWS services is excellent, providing flawless coordination with services such as SNS, S3, and Lambda.

I see scope for improvement in the drag-and-drop feature of AWS Glue. Beginners need additional support as it currently lacks some features required for complex transformations, often necessitating custom Python coding.

I have been using Glue for more than five years now.

Overall, the stability of AWS Glue is excellent. I would rate it a nine out of ten. Some network-related issues may arise. That said, they are rare and do not affect its functionality significantly.

Regarding scalability, AWS Glue is nearly perfect. I would rate it a nine out of ten, although there is always room for improvement.

AWS customer service is great, but there is room for improvement. The issue I face is the inconsistency in dealing with different customer service representatives for the same issue, which disrupts personal touch.

Neutral

On an organizational level, the pricing of AWS Glue does not pose a concern. It is in line with other ETL tools in the market. However, AWS Glue's cost to free-tier users is an issue because it is not entirely free, even for trial purposes.

I advise potential users to adopt AWS Glue primarily due to its user-friendly interface, extensive documentation, and seamless integration with other AWS services, making it ideal for data engineers.

I'd rate the solution nine out of ten.

In my role as the global lead for AWS solutions and offerings, we work with various clients, including large-scale clients, to adopt and implement AWS cloud offerings. 

Our primary focus revolves around cloud lift-and-shift migration, modernization, re-platforming, rehosting, data architecture, design strategy, and implementing generative AI-specific solutions across different industries such as banking, capital insurance, energy utilities, manufacturing, automotive, semiconductor, and aerospace and defense. 

For example, we have implemented AWS Glue at several client locations, utilizing its serverless data integration capabilities during the data discovery process, enterprise transformation, cleansing, transforming, and centralizing data.

AWS Glue has significantly improved our data quality, enhancing the data by removing duplicates and providing timely and efficient insights. 

It also aids in real-time data processing, reducing effort and cost due to its serverless architecture. These features ensure we maintain the highest level of scalability, reliability, and security compliance.

AWS Glue is fully managed, providing an easy-to-use integration environment to create, run, and monitor ETL jobs. It's broadly compatible and seamlessly integrates with other AWS services like Amazon S3, Redshift, and Athena. It's flexible with data integration, manages various data formats (JSON, ORC, CSV, etc.), and is serverless, eliminating the need for infrastructure management.

Its ease of use, cost-effectiveness, and highly secure architecture are some of the most valuable features.

There could be an enhanced way of managing pure metadata management or data cataloging. 

Additionally, while it covers a wide range of integrations with AWS services, integrating with certain additional or legacy products is not seamless and can be complex. 

Increasing support for more programming languages and improving advanced analytics capabilities could also be beneficial.

We have been working with AWS Glue for almost three-plus years now.

We haven't faced any stability issues with AWS Glue. It is a scalable solution, provided that the right design principles and workload management are implemented.

AWS Glue is a scalable solution due to its serverless architecture and efficient design.

My team handles interactions with AWS for technical support, ensuring our design architectures are scalable, flexible, and well-integrated. We often reach out to the AWS team to double-check our implementation mechanisms and guidelines.

Positive

The initial setup of AWS Glue is straightforward due to its serverless architecture and fully managed nature. Specific prerequisites need to be followed, such as setting up data sources, configuring IAM permissions, creating crawlers, and running ETL jobs.

My team escalates technical questions to AWS support, ensuring our design architectures are optimal. We have a partnership with AWS, and the technical team frequently reaches out to AWS for guidance on scalability, flexibility, and integration mechanisms.

We have seen an efficient process with AWS Glue, providing the right return on investment at the right time. It ensures efficiency for our clients, giving them the desired ROI within their expected timelines.

Follow the right design principles and involve AWS at the right time to leverage the most current features and offerings from AWS Glue. Ensuring the right architecture will mitigate any issues. I'd rate the solution eight out of ten.

One common use case is migrating data from one system to another.  So, mostly migrating data and data engineering, getting real-time or near-real-time data using Lambda functions and migrating big data from on-prem to the cloud for historical data before starting a project.

If you have the Fund Manager, you could use a fast processing engine, which is crucial for performance. 

I also like that you can add custom libraries like JAR files and use them. So, the ability to use a fast processing engine and embed basic jobs easily are significant advantages.

One area that could be improved is the ETL view. The drag-and-drop interface is not as user-friendly as some other ETL tools. 

Additionally, AWS Glue can sometimes be slow, especially when processing large datasets. It was sometimes a bit slow. Also, I couldn't directly use bucketed data. With Elastic Glue, you had to convert your data frames into the correct format before connecting them using the drag-and-drop interface. So that's something I didn't like because the conversion process wasn't straightforward. 

In future releases, I would like to see a feature that could trigger Glue pipeline using an API or something. 

I have experience with AWS Glue. I have about one year of experience in a professional setting, but I have also done some personal work with this solution.

Support was good, but I was working with a big client, so that might have influenced the experience. The response time was fast, we heard back from them within a day. 

Positive

I would rate my experience with the initial setup an eight out of ten, where one is difficult and ten is easy. 

The initial setup is not very complex. You can customize parameters like minimum and maximum for your needs. For me, it wasn't complex to deploy the solution. 

I'd rate it around six out of ten compared to other tools like Databricks.  

We use AWS Glue for ETL batch processing purposes.

The product has a valuable feature for data catalog.

The product is expensive for data streaming compared to EMR. This area needs improvement.

We have been using AWS Glue for one and a half years.

I rate the product's stability a ten out of ten.

We have five to six AWS Glue users. I rate its scalability a nine out of ten.

We have used Cloudera before. We switched to AWS Glue for better pricing, scalability, and innovation.

The initial setup is easy. I rate the process an eight or nine out of ten. It could be deployed on-premises and on the cloud as well. We have a team of five executives to carry out the implementation.

It is an expensive product. I rate its pricing a nine out of ten.

I rate AWS Glue a nine out of ten.

Currently, we are utilizing AWS Glue for various ETL workloads, specifically in the life sciences domain. Our primary objective is to acquire data from various sources. Then, we store it in Redshift. This is where the complete use case of AWS Glue comes into the picture.

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.

The solution could be cheaper. The price of the solution is an area that needs improvement.

I have been using AWS Glue in my organization for a year. I am an end-user and a customer of the solution.

It is a stable solution. We have not faced any issues in the past year, so it's pretty stable. Stability-wise, I rate it a ten out of ten.

The solution has proven to be scalable, and from my experience in the data engineering domain, I rate it an eight out of ten. It is worth noting that I may not be the most qualified person to provide a rating since I mostly manage and work on data-related tasks. Currently, approximately 20-25 people in our company use the solution.

I had no experience with the technical support team of AWS Glue.

Previously, I used Azure Data Factory. But I did not find it really helpful. And it was a bit complex. It was not that user-friendly. And I am much more comfortable with the AWS services as compared to Azure services.

The initial setup of the solution is straightforward, and I find it easy to implement. I rate the setup process a nine on a scale of one to ten, where ten is the easiest. As for the deployment process, we usually request our platform team to handle it, and they are quite efficient in deploying and managing the infrastructure. Although I am not directly involved in the deployment process, my understanding is that it can be completed in just a few hours with the help of two to three team members. Our platform team consists of data engineers, architects, and platform engineers who cater to the needs of various projects and products within the AWS ecosystem. Fortunately, the solution does not require any maintenance.

Price-wise, the solution is adequate, and we have no issues with it. We believe that the cost is justified given the number of users and the features it provides. Overall, it can be considered an average-priced tool. I would rate the solution a six or seven on a scale of one to ten, with ten being very expensive. Specifically, I rate its pricing a six out of ten.

Before choosing AWS Glue, I evaluated Azure Data Factory.

I would tell those planning to use AWS Glue to try it. I rate the overall solution a ten out of ten.

The best feature is the price point. It's pretty cheap as compared to other tools like Informatica, et cetera. That's why major companies are moving to the cloud and using Glue. At least, that's what I found.

The solution is stable and reliable.

You can scale the product if you need to. 

The monitoring is not that good. We'd like to see job progress be more clear. Right now, how we can view that is not that good. The is that mostly it is Python or Scala code based. The UX is lacking.

There is a bit of a learning curve, particularly during the setup process. 

More connectors should be included.

I've been using the solution for three years. 

The solution is very reliable. It's stable. There are no bugs or glitches It works just fine. 

The solution can scale very well. It's not a problem.

Technical support is okay. We tend to go to the partner if we have issues, and they'll go to WS if they need to.

I'm also familiar with Informatica. However, Glue is less expensive. 

In terms of the initial setup, the learning part was a little bit stiff. After that, it is okay. We didn't have any issues once we understood the process. 

We didn't require any outside assistance such as integrators or consultants. We were able to handle it ourselves. 

The price is very good. It's enticing people to move to the cloud. 

That said, I do not have exact information on pricing. 

I'm an AWS engineer. My company is a gold partner.

I'd rate the product eight out of ten. So far, it's quite good. I don't have any complaints.  

We are implementing a solution in AWS for one of our customers. It is more of a data analytics solution. We wanted to process data from different sources and put it into a central repository that can be used for any analysis or predictive modeling.

The most valuable feature of AWS Glue is scalability.

Since AWS Glue is not like an enterprise ETL tool, we need to put quite a lot of effort into customization. The solution has a visual editor, but most ETL transformations cannot be implemented or constructed using that. We always have to do a script. The solution's visual ETL tool is of no use for actual implementation.

I have been using AWS Glue for two years.

I rate AWS Glue an eight out of ten for stability.

Most of our clients for AWS Glue are enterprise businesses.

I rate AWS Glue ten out of ten for scalability.

Nobody from AWS technical support has implementation experience.

Neutral

On a scale from one to ten, where one is difficult and ten is easy, I rate the solution's configuration a five and its implementation a two or three out of ten.

The solution's pricing is pay-as-you-go. If you are using the solution for an enterprise business, it will be expensive.

AWS Glue is a cloud-based solution.

Overall, I rate AWS Glue a six out of ten.

I primarily use AWS Glue as a lightweight ETL to migrate our existing on-prem workloads to a cloud environment without looking at a lot of migration paths. 

AWS Glue served the purpose of migrating our on-prem workloads to a cloud environment without involving a heavy load. It ensured that we were able to test every migrated component independently.

AWS Glue's best features are scalability and cloud-based features.

AWS Glue would be improved by making it easier to switch from single to multi-cloud.

I've been using AWS Glue for eighteen months.

I would rate AWS Glue's scalability eight out of ten, as it still has some room to improve.

AWS Glue is straightforward to implement, and you won't see any technical complexity if you're from a development background.

We also considered Airflow, but Glue was a better fit for our engineering-heavy workloads because we wanted a serverless option.

I would rate AWS Glue eight out of ten.