AWS Glue

AWS Glue

AWS Glue

37 Reviews and Ratings

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
AWS Glue	Score 7.5 out of 10	N/A	AWS Glue is a managed extract, transform, and load (ETL) service designed to make it easy for customers to prepare and load data for analytics. With it, users can create and run an ETL job in the AWS Management Console. Users point AWS Glue to data stored on AWS, and AWS Glue discovers data and stores the associated metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once cataloged, data is immediately searchable, queryable, and available for ETL.	$0.44 billed per second, 1 minute minimum

Pricing

AWS Glue

Editions & Modules

per DPU-Hour: $0.44
billed per second, 1 minute minimum

Offerings

Pricing Offerings
AWS Glue
Free Trial
No
Free/Freemium Version
No
Premium Consulting/Integration Services
No

Entry-level Setup Fee

No setup fee

Additional Details

—

More Pricing Information

Community Pulse
	AWS Glue

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	AWS Glue
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User Ratings
	AWS Glue
Likelihood to Recommend	7.0 (0 ratings)
Usability	7.0 (0 ratings)
Support Rating	7.0 (0 ratings)

User Testimonials
	AWS Glue
Likelihood to Recommend	When the data which requires ETL has different formats, schema, and volume, this service suits them best. So, when the volume is not consistent (typical use-case of healthcare and online shopping), AWS Glue can be the prime choice. When the data is available in both batch and streaming mode, the developer needs to generate a separate codebase. This increases the source code management efforts. So, prefer to go with Glue when the nature of the data is the same (either batched or streamed). Incentivized Apurv Doshi Practice Head - Labs (Innovation and R&D) Read full review
Pros	After data cleansing, the team also implemented the best practices for using AWS platform services as a Data Lake, such as job bookmarking for AWS Glue jobs, proper delimiter for the AWS Glue crawlers, partitioning in AWS S3, and transformation to parquet file for compression and faster querying time in Amazon Athena. Data modernization through combining data from multiple sources into a functioning datasets, rebuilding DW, and resctructuring data sources. Aims to lessen customer complaints, eliminate manual data extraction requests via SR from different data sources, and Increase accuracy, consistency and speed up reconciliation process. Incentivized SC Sonny Carlos Head of Cloud and Data Business Read full review
Cons	It’s integration with other cloud vendors is bit difficult If it can support non SQL based databases as well, it would be powerful. Real time data synchronisation in data source is missing Incentivized Verified User Anonymous Read full review
Usability	I personally found it very usable for a data engineer's day job, particularly for performing ETL and managing the data pipelines. Incentivized Verified User Anonymous Read full review
Support Rating	Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios. Incentivized Verified User Anonymous Read full review
Alternatives Considered	The cataloging of data objects is the best in the case of AWS Glue. We use AWS Glue in all of our data pipelines to sync external and internal data sources and to automatically produce SQL-based ETL based on AWS Glue catalog objects. Integration with Amazon products is the other advantage. Incentivized Verified User Anonymous Read full review
Return on Investment	Positive Impact :- after ETL we can able to do some kind of automation Negative :- At some point of time it can hamper the cost but not really Incentivized Verified User Anonymous Read full review
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