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.
Site Reliability Engineer (AWS) at KFin Technologies Ltd
Real User
Top 10
2024-10-29T07:19:00Z
Oct 29, 2024
AWS Glue is highly recommended for data engineers due to its ability to build and maintain data pipelines, ensure data quality and integrity, and its integration with UI tools. It offers data preparation, machine learning integration, and governance. I would rate it a ten out of ten.
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.
Principal System Architect at a transportation company with 1,001-5,000 employees
Real User
Top 5
2024-09-06T15:45:25Z
Sep 6, 2024
AWS Glue is built for large datasets, and it does the job perfectly. I would recommend the solution to other users. Overall, I rate the solution eight and a half out of ten.
Glue is not a must-have tool. You can choose Glue if you have the capability to learn Glue as quickly as possible. There are other alternatives where you will find a lot of articles, study material, and certificates over the internet apart from Glue. If you do not have any other option, go for Glue. If Glue is not mandatory for you, go for something else because it is difficult to learn Glue and remember the syntaxes. You will need support whenever you have a bigger integration or connectivity with third-party libraries or services. You will not receive many articles or help over the internet. Although the community is available, you need to spend some time with them to make them understand the issue. It is not easy for a beginner to learn to use the solution for the first time. There are a few videos and courses available, but it's difficult. It's not as easy as other languages in terms of content. It's hard, but you can use it once you understand the concept. Overall, I rate the solution seven and a half out of ten.
AVP at a manufacturing company with 10,001+ employees
Real User
Top 5
2024-06-21T06:35:50Z
Jun 21, 2024
The main piece of AWS Glue is the ETL part. AWS Glue is for ETL to deal with S3 data sources to Redshift. We use AWS Glue for the CDC. As the product is serverless, the tool runs fine. Most of the maintenance and monitoring are among the biggest challenges of the tool. In terms of the product's ability to handle data volumes during scaling needs, I would say that though it offers the area of data volumes, the challenges are associated with costs. The latency would be there if the source had a huge amount of data coming in, and so based on it, it would read the source system sequentially because of the way the CDC works. If I need to capture the change in the source change in the order, it can happen, and if you have a better network, you can also scale up by bringing the source to S3 or AWS Glue. When you can scale up, it is not really relevant for the group. The latency is not because of AWS Glue but because when it comes to ETL or CDC, I need to process it the same way I do it with AWS Glue. I cannot do parallel processing, and I need to do it sequentially. I don't see any AI capabilities in the product, and it is more of an ETL solution. As the product has many problems, people are moving to Bare Metal and other cloud services. Our company has spent a lot of time investigating what AWS Glue does, including the time required to use it to maintain the servers. I need to spend on the product's maintenance along with the other activities for which I need to make payments to use the solution. Once you are able to predict the data volumes and other factors that are there over the cloud, it is possible to predict what my server will cost for the next five years and then get the servers at a very low price instead of depending on AWS. Though it is a good solution, it is not cost-sensitive. I rate the tool a six out of ten.
Two of us are sufficient for the solution’s maintenance. The solution is easy to set up and starts with a lot of standard data analytical use cases where we extract data. If you want something customizable, then look at other solutions because cost might be a factor for more advanced solutions. Overall, I rate the solution a seven out of ten.
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.
Senior Software Developer at a computer software company with 10,001+ employees
Real User
Top 10
2023-07-31T17:41:50Z
Jul 31, 2023
I would recommend that new users refer to the AWS documentation. The documentation is very well-written and easy to understand. Even new users with no prior experience with AWS should be able to get up and running quickly. I would also recommend that new users learn Python. Overall, I would rate the solution a nine out of ten.
Based on the customer scenario, I have previously recommended AWS Glue. Sometimes, customers directly request either Azure RapidAPI or AWS Glue. It depends on the specific business use case. Both tools have limitations, so it's hard to say which is best. If a customer already uses Microsoft products, I suggest going with Azure. As for a general rating, I would give AWS Glue a seven out of ten. Overall, I would rate AWS Glue a seven out of ten because it's not about performance. It's because of how the tool is used.
I'm using the latest version of AWS Glue. I'm not the end-user, as I work for a company that implements AWS Glue for clients. My company has one client using AWS Glue, but that client has three hundred million users. I recommend AWS Glue to others because it's an excellent solution. However, it lacks documentation. There's only a little documentation available. Even certified AWS practitioners struggle with the lack of documentation for AWS Glue. You'll find complicated processes or features, such as time series tables. Even if there's documentation, implementing the solution requires many trial and error methods, and revamping becomes a nightmare if you're using the old infrastructure. My rating for AWS Glue is seven out of ten because of the complexity of the deployment, and the lack of information and documentation, that my company had to do some R&D. If AWS had complete documentation, or sent more than one person to assist my company, then it could have saved more time.
CEO - Founder / Principal Data Scientist / Principal AI Architect at Kanayma LLC
Real User
2022-11-25T20:48:52Z
Nov 25, 2022
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.
ECM CONSULTANT/ARCHITECT/SOFTWARE DEVELOPER, DELUXE MN at a tech services company with 5,001-10,000 employees
Real User
2021-12-02T16:14:50Z
Dec 2, 2021
In that environment, there is a lot going on. There are some things that you can get for free, and there are some add-ons that you can develop or use that have been tested. It's all about convenience and service. You will get what you pay for if you pay for what you want. I'm not a fan of any tools; it all depends on the organization I work for, where their data is, what they want to do with it, how quickly they want to get there, and what their budget is, and you work around that. For me, I would not choose one over the other, unless I know the details of the project. I would rate AWS Glue a nine out of ten.
Team Lead at a financial services firm with 5,001-10,000 employees
Real User
2020-10-14T06:36:55Z
Oct 14, 2020
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.
AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.
AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates...
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.
AWS Glue is highly recommended for data engineers due to its ability to build and maintain data pipelines, ensure data quality and integrity, and its integration with UI tools. It offers data preparation, machine learning integration, and governance. I would rate it a ten out of ten.
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.
AWS Glue is built for large datasets, and it does the job perfectly. I would recommend the solution to other users. Overall, I rate the solution eight and a half out of ten.
Glue is not a must-have tool. You can choose Glue if you have the capability to learn Glue as quickly as possible. There are other alternatives where you will find a lot of articles, study material, and certificates over the internet apart from Glue. If you do not have any other option, go for Glue. If Glue is not mandatory for you, go for something else because it is difficult to learn Glue and remember the syntaxes. You will need support whenever you have a bigger integration or connectivity with third-party libraries or services. You will not receive many articles or help over the internet. Although the community is available, you need to spend some time with them to make them understand the issue. It is not easy for a beginner to learn to use the solution for the first time. There are a few videos and courses available, but it's difficult. It's not as easy as other languages in terms of content. It's hard, but you can use it once you understand the concept. Overall, I rate the solution seven and a half out of ten.
The main piece of AWS Glue is the ETL part. AWS Glue is for ETL to deal with S3 data sources to Redshift. We use AWS Glue for the CDC. As the product is serverless, the tool runs fine. Most of the maintenance and monitoring are among the biggest challenges of the tool. In terms of the product's ability to handle data volumes during scaling needs, I would say that though it offers the area of data volumes, the challenges are associated with costs. The latency would be there if the source had a huge amount of data coming in, and so based on it, it would read the source system sequentially because of the way the CDC works. If I need to capture the change in the source change in the order, it can happen, and if you have a better network, you can also scale up by bringing the source to S3 or AWS Glue. When you can scale up, it is not really relevant for the group. The latency is not because of AWS Glue but because when it comes to ETL or CDC, I need to process it the same way I do it with AWS Glue. I cannot do parallel processing, and I need to do it sequentially. I don't see any AI capabilities in the product, and it is more of an ETL solution. As the product has many problems, people are moving to Bare Metal and other cloud services. Our company has spent a lot of time investigating what AWS Glue does, including the time required to use it to maintain the servers. I need to spend on the product's maintenance along with the other activities for which I need to make payments to use the solution. Once you are able to predict the data volumes and other factors that are there over the cloud, it is possible to predict what my server will cost for the next five years and then get the servers at a very low price instead of depending on AWS. Though it is a good solution, it is not cost-sensitive. I rate the tool a six out of ten.
AWS Glue is a cloud-based solution. Overall, I rate AWS Glue a six out of ten.
Two of us are sufficient for the solution’s maintenance. The solution is easy to set up and starts with a lot of standard data analytical use cases where we extract data. If you want something customizable, then look at other solutions because cost might be a factor for more advanced solutions. Overall, I rate the solution a seven out of ten.
I rate AWS Glue an eight out of ten.
I rate AWS Glue a nine out of ten.
I'd rate it around six out of ten compared to other tools like Databricks.
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.
I rate the overall product an eight out of ten.
I would recommend that new users refer to the AWS documentation. The documentation is very well-written and easy to understand. Even new users with no prior experience with AWS should be able to get up and running quickly. I would also recommend that new users learn Python. Overall, I would rate the solution a nine out of ten.
Overall, I rate AWS Glue a seven out of ten.
Based on the customer scenario, I have previously recommended AWS Glue. Sometimes, customers directly request either Azure RapidAPI or AWS Glue. It depends on the specific business use case. Both tools have limitations, so it's hard to say which is best. If a customer already uses Microsoft products, I suggest going with Azure. As for a general rating, I would give AWS Glue a seven out of ten. Overall, I would rate AWS Glue a seven out of ten because it's not about performance. It's because of how the tool is used.
I would tell those planning to use AWS Glue to try it. I rate the overall solution a ten out of ten.
Overall, I would rate this product a seven out of ten. It is a good product, but I have not experienced all the additional features.
I'm using the latest version of AWS Glue. I'm not the end-user, as I work for a company that implements AWS Glue for clients. My company has one client using AWS Glue, but that client has three hundred million users. I recommend AWS Glue to others because it's an excellent solution. However, it lacks documentation. There's only a little documentation available. Even certified AWS practitioners struggle with the lack of documentation for AWS Glue. You'll find complicated processes or features, such as time series tables. Even if there's documentation, implementing the solution requires many trial and error methods, and revamping becomes a nightmare if you're using the old infrastructure. My rating for AWS Glue is seven out of ten because of the complexity of the deployment, and the lack of information and documentation, that my company had to do some R&D. If AWS had complete documentation, or sent more than one person to assist my company, then it could have saved more time.
I would rate AWS Glue a seven on a scale of one to ten.
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.
I would definitely recommend using AWS Glue for batching procedures. I would rate AWS Glue an eight out of ten.
I am moving to the EMR serverless or GCP solution. I rate AWS Glue a nine out of ten.
I would recommend this solution to others. I rate AWS Glue a nine out of ten.
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.
Before you start using it, you need to know PySpark. I would rate it a nine out of ten. It is good for what we are using it for.
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 would rate this solution a seven out of ten.
On a scale from one to ten, I would give AWS Glue a nine.
In that environment, there is a lot going on. There are some things that you can get for free, and there are some add-ons that you can develop or use that have been tested. It's all about convenience and service. You will get what you pay for if you pay for what you want. I'm not a fan of any tools; it all depends on the organization I work for, where their data is, what they want to do with it, how quickly they want to get there, and what their budget is, and you work around that. For me, I would not choose one over the other, unless I know the details of the project. I would rate AWS Glue a nine out of ten.
I rate AWS Glue as an eight out of ten.
I would rate AWS Glue a seven out of ten.
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.
I would recommend AWS Glue. It is a great choice. I would rate this solution a nine out of ten.