Table of contents
Fully Managed
AWS Glue is a fully managed ETL (Extract, Transform, Load) service, which means you don't need to manage any underlying infrastructure. This reduces the operational overhead and allows you to focus on the data processing tasks.
Scalability
AWS Glue can automatically scale resources up or down based on the demand and workload, ensuring optimal performance without manual intervention.
Serverless
Being serverless, there are no servers to manage or maintain. You only pay for the resources that you consume, which can result in significant cost savings.
Integrated Data Catalog
AWS Glue comes with a built-in data catalog that helps you organize and discover your data. It automatically indexes and maintains metadata about your data, making it easier to manage.
Support for Multiple Data Sources
AWS Glue supports a variety of data sources including Amazon S3, RDS, Redshift, and many external databases, providing flexibility in your ETL processes.
Developer Tools
AWS Glue provides developer endpoints for custom ETL logic, and integrates with AWS SDKs, Boto3, and the AWS CLI, allowing for a flexible development experience.
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AWS Glue is generally considered a good option for organizations looking for a powerful, scalable, and cost-effective ETL solution within the AWS ecosystem. Its ease of integration with AWS services, managed nature, and capability to handle large volumes of data make it a strong choice, particularly for teams that are already using AWS services.
We have collected here some useful links to help you find out if AWS Glue is good.
Check the traffic stats of AWS Glue on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of AWS Glue on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of AWS Glue's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of AWS Glue on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about AWS Glue on Reddit. This can help you find out how popualr the product is and what people think about it.
Managed Services: This includes the per-token costs of using services like Amazon Bedrock, the hosting fees for SageMaker endpoints, and the costs associated with data pipelines using services like Glue or Lambda. - Source: dev.to / 11 months ago
However, using any Iceberg engine traditionally requires a first, crucial step: setting up and configuring an Iceberg catalog. This catalog is responsible for managing the table metadata. While flexible, this often means provisioning and managing a separate service like AWS Glue, a dedicated PostgreSQL database for the JDBC catalog, or a REST service. This adds an extra layer of configuration and operational... - Source: dev.to / about 1 year ago
In this article, we present an architecture that demonstrates how to collect application logs from Amazon Elastic Kubernetes Service (Amazon EKS) via Vector, store them in Amazon Simple Storage Service (Amazon S3) for long-term retention, and finally query these logs using AWS Glue and Amazon Athena. - Source: dev.to / about 1 year ago
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to prepare and load data for analysis. It helps bridge the gap between our MongoDB Atlas data and the services we'll use for recommendation. - Source: dev.to / over 2 years ago
AWS Glue is a fully managed extract, transform, and load (ETL) service provided by Amazon Web Services (AWS). It is designed to make it easy for users to prepare and load their data for analysis. AWS Glue simplifies the process of building and managing ETL workflows by providing a serverless environment for running ETL jobs. - Source: dev.to / over 2 years ago
It is serverless data integration service to allow you to easily scale your workloads in preparing data and moving transformed data into a target location. - Source: dev.to / about 3 years ago
So in the next post, we'll do that: We'll take what we've done here, add a few more components with Pulumi and AWS Glue, and wire it all up with a few magical lines of Python scripting. - Source: dev.to / over 3 years ago
Once it's in a Data Lake then you have different options depending on the analytics you need. For more advanced constant analytics then you could look into Amazon Kinesis Data Analytics instead of Firehose to S3, but for Ad-Hoc queries then this is where Glue and Athena come in. - Source: dev.to / over 3 years ago
You will want to use metrics based on operations outcomes to gain useful insights. Now you want to do analytics on your logs and use Cloudwatch Logs Insights or store the logs in Amazon S3, which then triggers an AWS Glue crawler to create an AWS Glue Data Catalog that then can be queried using Amazon Athena using standard SQL. The results can be visualized in Amazon Quicksight. - Source: dev.to / over 3 years ago
Storing data in S3 has an additional benefit, given how well it integrates with other AWS services. For instance, you can use Amazon Athena to query your S3 data, or Amazon Rekognition to analyze it. Additionally you can use AWS Glue to perform extract, transform, and loan (ETL) operations. To create ad hoc visualizations and business analysis reports, Amazon QuickSight can connect to your S3 buckets and produce... - Source: dev.to / almost 4 years ago
Not 100% if this is what you need, but look into integrating AWS Glue. It should be able to keep the data source that Athena uses up to date real time or close to it, from what I understand. Source: about 4 years ago
AWS Glue streaming ETL (Extract Transform and Load) can now detect compressed data streaming from Amazon Kinesis, Amazon Managed Streaming for Apache Kafka (Amazon MSK), and self managed Apache Kafka. It can then automatically decompresses this data without customers having to write code, saving them development hours. AWS Glue Streaming ETL jobs continuously consume data from streaming sources, cleans and... - Source: dev.to / about 4 years ago
Use some ETL service from AWS and push what has been processed to a Log Group: AWS Glue is the service that can be used for this purpose. So it's another option to make everything inside the cloud itself. - Source: dev.to / about 4 years ago
Also, if you're doing this for an employer, and they have some deeper pockets, there is also AWS Data Pipeline. Source: over 4 years ago
Why aren't you looking at AWS Glue to load the data from Postgres to Redshift? It's relatively inexpensive and purpose built for such tasks. Source: over 4 years ago
AWS Glue is a fully managed ETL service that makes it simple and cost-effective to categorize, clean, enrich, and migrate data from a source system to a data store for ML. - Source: dev.to / over 4 years ago
Unfortunately there's just so many options for data ingest. Any programming language could be used, and there's plenty of off-the-shelf software and SaaS solutions to do it too. For example it could be done with AWS Data Pipeline (https://aws.amazon.com/datapipeline) or maybe there's just a EC2 virual machine running some custom python code that is doing it. Source: about 5 years ago
Looks like that is a ETL system, so https://aws.amazon.com/glue/. Source: over 5 years ago
AWS Glue, a serverless ETL (Extract, Transform, Load) service from Amazon Web Services (AWS), has captured significant attention in the data integration industry. Public opinion, as derived from recent articles and discussions, generally portrays AWS Glue as an efficient, flexible, and integrated solution particularly suited for organizations leveraging the AWS ecosystem.
Serverless Architecture: A consistent highlight across mentions is AWS Glue's serverless nature, which eliminates the need for infrastructure management. Users appreciate that AWS automatically provisions and de-provisions servers as needed, streamlining operations and reducing overhead.
Deep AWS Integration: AWS Glue's seamless integration with other AWS services is frequently cited as a major advantage. This integration is particularly beneficial for AWS-centric data teams, allowing for close interaction with services like Amazon S3, Amazon Redshift, Amazon Athena, and more.
Flexibility and Versatility: The service is noted for its versatile tooling options, offering a choice between a drag-and-drop interface, Jupyter notebooks, or writing code in Python or Scala. This flexibility appeals to a wide array of users, from those seeking simplicity to developers needing advanced scripting capabilities.
Comprehensive ETL Capabilities: AWS Glue supports a wide range of data processing needs, including ETL, ELT, batch, and streaming workloads. The newly introduced features, such as automatic decompression for streaming ETL jobs, enhance its capability to handle real-time data efficiently.
Ease of Use and Automation: Job scheduling, automatic scaling, and AWS Glue Data Catalog facilities are appreciated for simplifying data workflows and enabling efficient data cataloging and query optimizations over time through an extended history of schema versions.
AWS Glue is seen as ideal for organizations managing large-scale data projects that require robust ETL processes without infrastructure hassle. Companies benefit from its automated features for data cleaning, enrichment, and movement, particularly in scenarios like migrating data from PostgreSQL to Redshift or integrating with services like MongoDB and Amazon Personalize.
Articles and user discussions often position AWS Glue favorably compared to its competitors like Xplenty, Talend, and Stitch due to its serverless nature and deep integration within AWS.
While AWS Glue receives praise for its capabilities and integration, some potential users might find its deep embedding into AWS a limitation, particularly those operating in multi-cloud environments. The product is best positioned for those already invested in or open to adopting AWS services broadly.
AWS Glue stands out as an adept choice for AWS-centered organizations seeking a powerful, scalable, and integrated ETL solution. The service meets varying data processing needs while offloading infrastructure management, aligning with businesses aiming to maximize their AWS investments. Its comprehensive toolset and automation potentials continue to garner positive feedback from data engineers and analysts in the cloud computing sphere.
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Is AWS Glue good? This is an informative page that will help you find out. Moreover, you can review and discuss AWS Glue here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.
