Amazon S3 Glacier vs. Azure Data Lake Storage

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon S3 Glacier
Score 9.0 out of 10
N/A
The Amazon S3 Glacier storage classes are purpose-built for data archiving, providing a low cost archive storage in the cloud. According to AWS, S3 Glacier storage classes provide virtually unlimited scalability and are designed for 99.999999999% (11 nines) of data durability, and they provide fast access to archive data and low cost.
$0
Per GB Per Month
Azure Data Lake Storage
Score 8.2 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
Amazon S3 GlacierAzure Data Lake Storage
Editions & Modules
Bulk Retrieval Pricing
$0.0025
Per GB Per Month
Storage Pricing
$0.004
Per GB Per Month
Retrieval Pricing
$0.01
Per GB Per Month
Expedited Retrieval Pricing
$0.03
Per GB Per Month
No answers on this topic
Offerings
Pricing Offerings
Amazon S3 GlacierAzure Data Lake Storage
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon S3 GlacierAzure Data Lake Storage
Considered Both Products
Amazon S3 Glacier
Chose Amazon S3 Glacier
We only compared the costs but as most of our machines and services are AWS centric and final call was with client so they decided to go with AWS Glacier only.
Chose Amazon S3 Glacier
Amazon Glacier isn't a direct competitor to the products I've listed; it could compare to the clouds/data warehouses each of these products use to store their data. In the case of CloudBerry, Amazon Glacier is used with it to create a complete archival backup system. That …
Chose Amazon S3 Glacier
Glacier is convenient with systems already on AWS and cheaper than S3 for data that needs to be accessed infrequently. A great tool for any team to use that has a legacy system or data.
Chose Amazon S3 Glacier
Since the rest of our infrastructure is in Amazon AWS, coding for sending data to Glacier just makes sense. The others are great as well, for their specific needs and uses, but having *another* third-party software to manage, be billed for, and learn/utilize can be costly in …
Chose Amazon S3 Glacier
The other alternatives for us would involve moving objects out of S3 to some other object storage services, which would generate a lot of network traffic, or keep the objects on more expensive storage.
Chose Amazon S3 Glacier
It is significantly cheaper than other services, however, it is because it actually is a slightly different service. The other services we've tried allow live reading/writing of data as needed, whereas Glacier is a "cold storage" service. So essentially your choice ends up …
Azure Data Lake Storage
Chose Azure Data Lake Storage
We have used both Hadoop and GCS buckets for our storage needs of very large healthcare data. In terms of comparison with the Hadoop distributed Files system, Azure Data Lake Storage always stands in a far better position due to easy integration with various latest and widely …
Chose Azure Data Lake Storage
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 …
Chose Azure Data Lake Storage
We chose Azure Data Lake due to the fact that it was already a product under the Azure application suite. We didn't have to focus on integrating another 3rd party application within our environment. Also due to the fact Azure Data Lake scales its storage pools very efficiently, …
Chose Azure Data Lake Storage
We decided long ago to develop for the Azure platform, so we only evaluate products from within Azure. And Azure Data Lake Storage is really the dominant offering within its space. But to give you a comparison, previously we used to use Azure SQL Database for our analytical …
Chose Azure Data Lake Storage
Microsoft solutions provide great harmony in end-to-end data value creation, and Azure Data Lake Storage is highly compatible with other analytical solutions, e.g., Azure Data Factory and Databricks. So I would say that it is at the heart of the analytical solution in the …
Chose Azure Data Lake Storage
Snowflake, Apache Hive, Google BigQuery, Alteryx and Databricks Lakehouse Platform (Unified Analytics Platform)
Chose Azure Data Lake Storage
AWS charges you on an hourly basis but Azure has a pricing model of per minute charge. In terms of short term subscriptions, Azure has more flexibility but it is more expensive. Azure has a much better hybrid cloud support in comparison with AWS. AWS provides direct connections …
Chose Azure Data Lake Storage
I am much more familiar with Snowflake. I thought it was fairly straightforward to use and did not have to learn much syntax. With Azure Data Lake Storage, I have had to learn some new syntax and thought there was a steeper learning curve. We selected it because of cost savings.
Chose Azure Data Lake Storage
Simpler to use, in my opinion. It is also slightly cheaper.
Chose Azure Data Lake Storage
We looked at the Amazon solution and it did not play as well with our existing tools and added a layer of maintenance that we were not willing to take on at the time. We thought that our Microsoft contract and support were good and that our internal team had the knowledge to …
Chose Azure Data Lake Storage
The Azure Data Lake solution is designed for organizations that want to take advantage of big data. It provides a data platform that can help developers, data scientists, and analysts store data of any size and format and perform all types of processing and analytics across …
Best Alternatives
Amazon S3 GlacierAzure Data Lake Storage
Small Businesses
Cove Data Protection
Cove Data Protection
Score 9.1 out of 10
Amazon S3 Glacier
Amazon S3 Glacier
Score 9.0 out of 10
Medium-sized Companies
Cove Data Protection
Cove Data Protection
Score 9.1 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.9 out of 10
Enterprises
Microsoft Exchange
Microsoft Exchange
Score 8.7 out of 10
Azure Blob Storage
Azure Blob Storage
Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon S3 GlacierAzure Data Lake Storage
Likelihood to Recommend
9.0
(0 ratings)
8.2
(0 ratings)
Usability
6.0
(0 ratings)
-
(0 ratings)
User Testimonials
Amazon S3 GlacierAzure Data Lake Storage
Likelihood to Recommend
As described in the use case, it is perfect for backup data storage where you do not expect to retrieve the data often. Think of it as a data dump; it is nice to know you have a backup, but it actually is expensive and somewhat difficult to retrieve everything.
Read full review
Azure Data Lake storage is well suited for applications/use cases within organizations where capturing and storing large amounts of data in any format is required, primarily for storing and processing purposes. It's an easy and cost-effective cloud solution for your application data. The ability to integrate with other Azure Services like Azure Databricks and Azure Data Factory is superb.
Read full review
Pros
  • Glacier is an inexpensive solution to the problem of storing rarely-accessed data for years.
  • You can configure S3 buckets to transition objects to Glacier with a few clicks.
  • It is easy to get started with Glacier; there is little learning curve and few concepts to familiarize yourself with.
Read full review
  • Azure Data Lake Storage is extremely scalable. It allows us to scale up or down endlessly based on what we need including replication.
  • In terms of security, Azure Data Lake Storage fits our requirements really well as we can monitor and encrypt seamlessly. We can also assign permissions through roles and grant network-level access.
  • Due to the fact that it can scale, we are able to monitor the cost of storage and any given time and make financial decisions about our infrastructure based on how small or big we want to scale.
Read full review
Cons
  • Billing system isn't the smoothest to operate
  • Recalling information from glacier can run slow depending on type of data
  • Customer support
Read full review
  • I'd like to see a better cross-platform native client. Azure Data Explorer is fine, but it's far from the "SSMS" kind of experience SQL Server users are used to.
  • Listing a large number of file is somewhat problematic and slow. Using the native C# library, running directly on an Azure VM, it can take several hours to list just a couple million files.
  • Switching from V1 to V2 requires the creation of a new Storage Account and that's pretty inconvenient.
Read full review
Usability
It is difficult to delete the data as you have to wait for inventory and then bucket modification has to expire.
Read full review
No answers on this topic
Alternatives Considered
Amazon Glacier isn't a direct competitor to the products I've listed; it could compare to the clouds/data warehouses each of these products use to store their data. In the case of CloudBerry, Amazon Glacier is used with it to create a complete archival backup system. That said, when using Amazon Glacier along with a product like CloudBerry, you can create a reliable, inexpensive cloud backup system for retaining HUGE quantities of data for much less than these other cloud backup solutions. HOWEVER, if you want to restore said data, the cost and complexity begin to become a major concern, so Amazon Glacier should only be considered in situations where you don't plan to touch the data regularly, if at all, once it's at Glacier.
Read full review
The Azure Data Lake solution is designed for organizations that want to take advantage of big data. It provides a data platform that can help developers, data scientists, and analysts store data of any size and format and perform all types of processing and analytics across multiple platforms and programming languages. It can work with your existing solutions, such as identity management and security solutions. It also integrates with other data warehouses and cloud environments. It can be useful for organizations that need the above softwares.
Read full review
Return on Investment
  • With this now we are storing data for less cost as compare to what we were paying earlier
  • Increased the data access limits
Read full review
  • The cost can be high for more advanced work. In some cases, for instance, time limits and lab runtimes may be too short if you are too slow to learn what is explained as you go along.
  • promote flexible team communication. You can create different spaces for different teams, and share files and tasks.
Read full review
ScreenShots