AWS Glue vs. Azure Data Lake Storage

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS Glue
Score 8.1 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
Azure Data Lake Storage
Score 8.9 out of 10
N/A
Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you speed your time to insight. Data Lake Storage Gen2 extends Azure Blob Storage capabilities and is optimized for analytics workloads.N/A
Pricing
AWS GlueAzure Data Lake Storage
Editions & Modules
per DPU-Hour
$0.44
billed per second, 1 minute minimum
No answers on this topic
Offerings
Pricing Offerings
AWS GlueAzure Data Lake Storage
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
AWS GlueAzure Data Lake Storage
Best Alternatives
AWS GlueAzure Data Lake Storage
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Amazon S3 Glacier
Amazon S3 Glacier
Score 9.3 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.7 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
AWS GlueAzure Data Lake Storage
Likelihood to Recommend
7.0
(8 ratings)
8.2
(13 ratings)
Usability
7.0
(1 ratings)
-
(0 ratings)
Support Rating
7.0
(1 ratings)
-
(0 ratings)
User Testimonials
AWS GlueAzure Data Lake Storage
Likelihood to Recommend
Amazon AWS
One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.
Read full review
Microsoft
Azure Data Lake is an absolutely essential piece of a modern data and analytics platform. Over the past 2 years, our usage of Azure Data Lake as a reporting source has continued to grow and far exceeds more traditional sources like MS SQL, Oracle, etc.
Read full review
Pros
Amazon AWS
  • It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it.
  • As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues.
  • It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier.
Read full review
Microsoft
  • Setting up Azure Data Lake Storage account, container is quite easy
  • Access from anywhere and easy maintenance
  • Integration with Azure Data Factory service for end to end pipeline is pretty easy
  • Can store Any form of data (Structured, Unstructured, Semi) in faster manner
Read full review
Cons
Amazon AWS
  • In-Stream schema registries feature people can not use this more efficiently
  • in Connections feature they can add more connectors as well
  • The crucial problem with AWS Glue is that it only works with AWS.
Read full review
Microsoft
  • study for the certifications also to have them as a reference for work when you have any questions about applying a configuration to the equipment.
  • The Internet interface is simple and easy to use. Capacity is good and it's good that HP continues to innovate with this technology
Read full review
Usability
Amazon AWS
We give 7 rating because of usefulness in AWS world without worrying about infrastructure and services interaction, it’s pretty out of the box gives us the flexibility to interact with them and use them. we take the data source in s3 from external system and then transform it using other AWS services and putting it back for other external services to consume in S3 form.
Read full review
Microsoft
No answers on this topic
Support Rating
Amazon AWS
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.
Read full review
Microsoft
No answers on this topic
Alternatives Considered
Amazon AWS
AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.
Read full review
Microsoft
Azure Data Lake Storage from a functionality perspective is a much easier solution to work with. It's implementation from Amazon EMR went smooth, and continued usage is definitely better. However, Amazon EMR was significantly cheaper overall between the high transaction fees and cost of storage due to growth. The two both have their advantages and disadvantages, but the functionality of Azure Data Lake Storage outweighed it's cost
Read full review
Return on Investment
Amazon AWS
  • It had a positive impact on the way we build our data lake.
  • It is the single source of truth for data structure (schemas/tables/views).
Read full review
Microsoft
  • Instead of having separate pools of storage for data we are now operating on a single layer platform which has cut down on time spent on maintaining those separate pools.
  • We have had more of an ROI with the scalability as we are able to control costs of storage when need be.
  • We are able to operate in a more streamlined approach as we are able to stay within the Azure suite of products and integrate seamlessly with the rest of the applications in our cloud-based infrastructure
Read full review
ScreenShots