Amazon S3 is a cloud-based object storage service from Amazon Web Services. It's key features are storage management and monitoring, access management and security, data querying, and data transfer.
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Azure Data Factory
Score 8.3 out of 10
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Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.
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Pricing
Amazon S3 (Simple Storage Service)
Azure Data Factory
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon S3
Azure Data Factory
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Amazon S3 (Simple Storage Service)
Azure Data Factory
Features
Amazon S3 (Simple Storage Service)
Azure Data Factory
Data Center Backup
Comparison of Data Center Backup features of Product A and Product B
Amazon S3 (Simple Storage Service)
8.8
11 Ratings
2% above category average
Azure Data Factory
-
Ratings
Universal recovery
8.710 Ratings
00 Ratings
Instant recovery
8.210 Ratings
00 Ratings
Recovery verification
8.37 Ratings
00 Ratings
Business application protection
8.57 Ratings
00 Ratings
Multiple backup destinations
8.710 Ratings
00 Ratings
Incremental backup identification
9.24 Ratings
00 Ratings
Backup to the cloud
8.911 Ratings
00 Ratings
Deduplication and file compression
8.95 Ratings
00 Ratings
Snapshots
9.17 Ratings
00 Ratings
Flexible deployment
9.111 Ratings
00 Ratings
Management dashboard
7.910 Ratings
00 Ratings
Platform support
8.710 Ratings
00 Ratings
Retention options
9.57 Ratings
00 Ratings
Encryption
9.78 Ratings
00 Ratings
Enterprise Backup
Comparison of Enterprise Backup features of Product A and Product B
Amazon S3 (Simple Storage Service)
8.7
11 Ratings
3% above category average
Azure Data Factory
-
Ratings
Continuous data protection
9.410 Ratings
00 Ratings
Replication
8.810 Ratings
00 Ratings
Operational reporting and analytics
8.111 Ratings
00 Ratings
Malware protection
8.74 Ratings
00 Ratings
Multi-location capabilities
9.011 Ratings
00 Ratings
Ransomware Recovery
8.01 Ratings
00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Amazon S3 (Simple Storage Service)
-
Ratings
Azure Data Factory
8.1
8 Ratings
1% below category average
Connect to traditional data sources
00 Ratings
9.08 Ratings
Connecto to Big Data and NoSQL
00 Ratings
7.18 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Amazon S3 (Simple Storage Service)
-
Ratings
Azure Data Factory
8.0
8 Ratings
1% below category average
Simple transformations
00 Ratings
9.08 Ratings
Complex transformations
00 Ratings
7.08 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Amazon S3 (Simple Storage Service)
-
Ratings
Azure Data Factory
7.2
8 Ratings
8% below category average
Data model creation
00 Ratings
7.06 Ratings
Metadata management
00 Ratings
7.07 Ratings
Business rules and workflow
00 Ratings
7.08 Ratings
Collaboration
00 Ratings
7.97 Ratings
Testing and debugging
00 Ratings
6.18 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Amazon S3 is a great service to safely backup your data where redundancy is guaranteed and the cost is fair. We use Amazon S3 for data that we backup and hope we never need to access but in the case of a catastrophic or even small slip of the finger with the delete command we know our data and our client's data is safely backed up by Amazon S3. Transferring data into Amazon S3 is free but transferring data out has an associated, albeit low, cost per GB. This needs to be kept in mind if you plan on transferring out a lot of data frequently. There may be other cost effective options although Amazon S3 prices are really low per GB. Transferring 150TB would cost approximately $50 per month.
Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.
Fantastic developer API, including AWS command line and library utilities.
Strong integration with the AWS ecosystem, especially with regards to access permissions.
It's astoundingly stable- you can trust it'll stay online and available for anywhere in the world.
Its static website hosting feature is a hidden gem-- it provides perhaps the cheapest, most stable, most high-performing static web hosting available in PaaS.
It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
We can use linked service in multiple pipeline/data load.
It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.
Web console can be very confusing and challenging to use, especially for new users
Bucket policies are very flexible, but the composability of the security rules can be very confusing to get right, often leading to security rules in use on buckets other than what you believe they are
It is tricky to get it all set up correctly with policies and getting the IAM settings right. There is also a lot of lifecycle config you can do in terms of moving data to cold/glacier storage. It is also not to be confused with being a OneDrive or SharePoint replacement, they each have their own place in our environment, and S3 is used more by the IT team and accessed by our PHP applications. It is not necessarily used by an average everyday user for storing their pictures or documents, etc.
So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.
AWS has always been quick to resolve any support ticket raised. S3 is no exception. We have only ever used it once to get a clarification regarding the costs involved when data is transferred between S3 and other AWS services or the public internet. We got a response from AWS support team within a day.
We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue
Overall, we found that Amazon S3 provided a lot of backend features Google Cloud Storage (GCS) simply couldn't compare to. GCS was way more expensive and really did not live up to it. In terms of setup, Google Cloud Storage may have Amazon S3 beat, however, as it is more of a pseudo advanced version of Google Drive, that was not a hard feat for it to achieve. Overall, evaluating GCS, in comparison to S3, was an utter disappointment.
The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.
It practically eliminated some real heavy storage servers from our premises and reduced maintenance cost.
The excellent durability and reliability make sure the return of money you invested in.
If the objects which are not active or stale, one needs to remove them. Those objects keep adding cost to each billing cycle. If you are handling a really big infrastructure, sometimes this creates quite a huge bill for preserving un-necessary objects/documents.