Amazon S3 Glacier vs. Apache Hadoop

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon S3 Glacier
Score 9.1 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
Hadoop
Score 7.8 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
Pricing
Amazon S3 GlacierApache Hadoop
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 GlacierHadoop
Free Trial
YesNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon S3 GlacierApache Hadoop
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Amazon S3 GlacierApache Hadoop
Small Businesses
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Score 9.8 out of 10

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Medium-sized Companies
Cove Data Protection
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Score 9.8 out of 10
Cloudera Manager
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Score 9.9 out of 10
Enterprises
Microsoft Exchange
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Score 8.7 out of 10
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Score 8.5 out of 10
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User Ratings
Amazon S3 GlacierApache Hadoop
Likelihood to Recommend
9.0
(8 ratings)
8.0
(37 ratings)
Likelihood to Renew
-
(0 ratings)
9.6
(8 ratings)
Usability
6.0
(1 ratings)
8.0
(6 ratings)
Performance
-
(0 ratings)
8.0
(1 ratings)
Support Rating
-
(0 ratings)
7.5
(3 ratings)
Online Training
-
(0 ratings)
6.1
(2 ratings)
User Testimonials
Amazon S3 GlacierApache Hadoop
Likelihood to Recommend
Amazon AWS
If your organization has a lot of archival data that it needs to be backed up for safekeeping, where it won't be touched except in a dire emergency, Amazon Glacier is perfect. In our case, we had a client that generates many TB of video and photo data at annual events and wanted to retain ALL of it, pre- and post- edit for potential use in a future museum. Using the Snowball device, we were able to move hundreds of TB of existing media data that was previously housed on multiple Thunderbolt drives, external RAIDs, etc, in an organized manner, to Amazon Glacier. Then, we were able to setup CloudBerry Backup on their production computers to continually backup any new media that they generated during their annual events.
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Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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Pros
Amazon AWS
  • Cheap storage of backup data.
  • Can be used as a part of the entire suite of tools from Amazon, without requiring you to leave the familiar stack.
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Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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Cons
Amazon AWS
  • Sometime due to slow drives there are operation failure noticed by us in testing
  • Cost of restoring data is high and if you have regular restoring them it is not good option and slow as well.
  • While we were setting up the system we took some support from AWS and in many cases their answers were not up to the mark.
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Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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Likelihood to Renew
Amazon AWS
No answers on this topic
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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Usability
Amazon AWS
It is difficult to delete the data as you have to wait for inventory and then bucket modification has to expire.
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Apache
As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
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Support Rating
Amazon AWS
No answers on this topic
Apache
It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
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Online Training
Amazon AWS
No answers on this topic
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Alternatives Considered
Amazon AWS
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 money and time.
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Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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Return on Investment
Amazon AWS
  • We seldom need to access our data in Glacier; this means that it is a fraction of the cost of S3, including the infrequent-access storage class.
  • Transitioning data to Glacier is managed by AWS. We don't need our engineers to build or maintain log pipelines.
  • Configuring lifecycle policies for S3 and Glacier is simple; it takes our engineers very little time, and there is little risk of errant configuration.
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Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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