AWS Glue Reviews

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.

We use AWS Glue for data analytics.

AWS Glue is a stable and easy-to-use solution.

The solution’s stability could be improved.

I have been using AWS Glue for the last three years.

I rate AWS Glue a seven out of ten for stability.

AWS Glue is a very scalable solution, and you can connect multiple databases.

AWS Glue's technical support is very good.

AWS Glue is not a licensed solution. AWS Glue follows a pay-as-you-go model, wherein the cost of the data you use will be counted as a monthly bill.

Currently, there are many ETL tools in the marketplace. Compared to other ETL tools, AWS Glue is a low-cost and serverless solution.

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

We use the solution to do the usual type of transformations that before required ETL. It's mostly transformation-type purposes that we have, including transforming data from source to target. Also, we are replacing the usual ETLs with Glue, for example.

The solution has helped the organization mostly with migration. When we migrate from mostly on-premises to the cloud, Glue replaces a more expensive item that's also available in the cloud. Lots of programmers can understand Glue because they can write scripts in Python and PySpark, and there are quite a few programmers that know how to program in those languages. With the previous components that did similar things on-premise, you needed specialized knowledge.

The fact that we can use PySpark to program them is great. 

It's fairly straightforward as a product; it's not very complicated. 

The fact that Amazon offers it and it's a quick way of getting things done, and the fact that it doesn't require a lot of training is very positive attributes.

The initial setup is straightforward.  

It can scale.

The mapping area and the use of the data catalog from Glue could be better. I would say those two are the main things we'd like to see improvements on.

The solution needs support for big data.

As I understand it, Glue is based on Lambdas and Lambdas have some limitations as far as running them continuously. Sometimes they get dropped, and they have to be reinitialized.

I've been using the solution for about two years. 

So far, the solution has been stable. For everything that we've done, we didn't run into any problems, so it was fairly stable for us.

The solution can scale. I don't know exactly at what scale. I was using it for a medium-scale type solution. We never tested it with extremely large scales, so I don't know how expansive it can be. That said, since it's in the cloud, if you need more scale, it would be easy enough to add additional Glue components. At least, in theory, it should be fairly scalable.

Indirectly, we have hundreds of people on the solution. 

At this time, I'm not sure if any clients plan to increase usage. 

Since the solution is so easy to use, we have not needed the help of technical support. 

We've previously used many different solutions, including Informatica, Data Storage from IBM, and SSIS.

The solution is easy to set up. It's not overly complex.

At a minimum, a company would need one to two people to handle the deployment. If it is a larger scale of deployment, they might need more personnel. 

As a consultant, I assist with the implementation. 

Likely, a company would receive an ROI as it's cheaper than the alternatives.

I was not involved in the cost negotiation process. 

Our clients typically have chosen Glue from the start. I was not involved in the evaluation process. 

We are using one of the latest versions of the solution. It's about two years old. 

Depending on the number of data sources, the variety of data sources, and the variety of targets they will have, I might recommend the solution. What they have and plan to do will dictate whether Glue is a good solution or whether they would require something more sophisticated - such as Databricks. For example, if you have big data, then Databricks is probably a better solution to do ETL.

I'd rate the solution seven 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.

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.

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.

My colleagues work with Spark, PySpark, and Scala as programming languages for writing complex aggregations. They have a repository in order to have a general view of all the sources and jobs on the platform and AWS Glue is very helpful.

AWS Glue is a good solution for developers, they have the ability to write code in different languages and other software.

The interface for AWS Glue could improve, they do not put a lot of details. You can write the code, in PySpark or in Scala, which is a big advantage, it is only easy to use for a developer. It will be difficult for new users to enter the cloud environment.

If business users want to run their own graphs they will not have the opportunity to use such features, such as running code inside AWS Glue in Spark, which will be complex for them.

 I have been using AWS Glue for approximately four years.

AWS Glue is a highly stable solution. We didn't have bugs in production. 

The solution works well with Spark, which is a good framework for large volumes of data. It operates very well.

I rate the stability of AWS Glue a ten out of ten.

The scalability of AWS Glue is great. It was used for enterprise customers. We worked a lot with AWS Glue for International companies.

We have approximately 10 people using AWS Glue in my company.

I have to use the support from AWS Glue. The response time could improve.

I rate the support from AWS Glue a nine out of ten.

Positive

The initial setup of AWS Glue is very simple.

AWS Glue uses a pay-as-you-go approach which is helpful. The price of the overall solution is low and is a great advantage.

If I can compare AWS Glue to other solutions, it has the advantage of the cloud, which assures availability and scalability, and the pay-as-you-go is beneficial. This is why many companies are moving from their traditional ETL tools to the cloud because the costs will be reduced dramatically.

I would recommend this solution to others.

I rate AWS Glue a nine out of ten.

AWS Glue is fast and managed by AWS. Hence, you don't have to worry about capacity and the performance of Glue jobs. It has integrations with other data stores of AWS. The product offers metadata management, logging, and ETL processing capabilities. It comes with a powerful feature, Glue Studio, which helps to do queries interactively within the community. It is a managed service and very secure. Another popular and mature service is S3. 

I have encountered challenges with multi-region support. 

AWS Glue has standard procedures for tech support. 

Positive

AWS Glue is very user-friendly. However, if you are not a UI person, you can do IaaS. AWS provides a cloud automation service and a service catalog. 

I rate the tool's pricing a four out of ten. 

I rate AWS Glue an eight out of ten.