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 Lake Storage
Score 9.6 out of 10
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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.
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Pricing
Amazon S3 (Simple Storage Service)
Azure Data Lake Storage
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Offerings
Pricing Offerings
Amazon S3
Azure Data Lake Storage
Free Trial
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Free/Freemium Version
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Premium Consulting/Integration Services
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No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
Amazon S3 (Simple Storage Service)
Azure Data Lake Storage
Considered Both Products
Amazon S3
Verified User
Anonymous
Chose Amazon S3
S3 is excellent but has a different use case than ebs. As ebs can be used as a filesystem, s3 bucket stores objects
We opted for Amazon S3 (Simple Storage Service) solution as most of our workloads run on AWS and this saves as bandwidth costs. Otherwise the solutions are similar in capabilities for our needs.
Amazon S3 integrates way better with other AWS services and tools, making it the quick choice for your AWS based application. Furthermore, the pricing for Amazon S3 is very competitive and it has all the security and access capabilities to enable your application. Google …
Pricing and Cost Structure are best:Amazon S3:Offers multiple storage classes: Standard, Intelligent-Tiering, Standard-IA (Infrequent Access), One Zone-IA, Glacier, and Glacier Deep Archive while other were costly and figuring out the monthly costs were difficult. The …
Amazon S3 has so much other functionality than it's competitors with so many more use cases. We use One Drive, Drop Box, Teams, Google Drive and other products for basic file sharing while working with partners and clients but that's kind of the extent of those products. S3 …
More robust and feature rich. Also more cost effective. However, the other options do lend themselves to be better at user friendliness. But if your technological and willing to look up help in the support knowledgebase you will do just fine and get a better product at …
When we were implementation the solution of our issue then we find Azure and Google Cloud Storage platforms but we were unable to find the proper documentation for the platform as compared to S3, So we moved to S3 and discarded the other options. Cost wise there are only some …
Amazon S3 (Simple Storage Service) is the only AWS offering for object storage. DynamoDB is fantastic for unstructured data but does not handle object storage. The relational database service (RDS) is excellent but only applies to use cases with structured table data, and does …
All other alternatives are also good but as our infrastructure was on AWS, Amazon S3 (Simple Storage Service) was a better choice due to its better integration with other AWS services. It was serving the purpose in an economical way. All of our needs were being fulfilled by …
Amazon S3 is the business driving arrangement by Amazon Web Services. It has answers for all startup's and huge venture. The expense viability is one reason that I have chosen the Amazon S3 over other
We are an AWS shop, thus it is much easier to use with other AWS services. It may not always be the cheapest but once you are in AWS if you can decouple your apps and use this as one of your services it will certainly make developer's life easier and admin life easier.
S3 is the most mature simple storage service on the web. It has direct competitors from Google and Azure, as well as a bunch of other competitors that focus on different aspects. For example, Backblaze specializes on file backups, and while s3 can also be used for that, …
We had already decided to use Amazon S3 (Simple Storage Service) for other compute services, so it made sense to use Amazon for blob storage as well. By using the same cloud vendor, we can more easily integrate between AWS services like Cloudfront. Blob storage is essentially a …
Amazon S3 provides a variety of tools for uploading short and large objects to the cloud. AWS S3 is a key-value store, one of the major categories of NoSQL databases used for accumulating voluminous, mutating, unstructured, or semistructured data. S3 object retrieval is fast. …
They're both great. I really don't know the differences, but both have the same basic set of features, in my opinion. But, S3 is widely know as a greater tool, safer, and much easier. Also, it's used by and compatible with a lot of applications around the world. That made us …
I think [Amazon S3 (Simple Storage Service)] is cheaper than Azure Blob Storage (at least at the time I selected it). It is a low maintenance product and it is more reliable.
The main differences are that S3 files can be accessed publicly without having an account on the service so it is suitable for website assets, but the other services have desktop hard drive syncing applications so they are more suitable for sharing files to other staff in the …
Google Cloud Storage provides many of the same features as Amazon S3 (Simple Storage Service), but they differ quite a bit in the database integrations they provide. The main reason we had to use Amazon S3 (Simple Storage Service) is because our main infrastructure cloud …
AWS probably has the most difficult UI to learn but it's the far better service. Google is probably second but it has storage limitations and there are some security concerns (still a good tool for collaboration) The Microsoft products are the worst IMO. They're slow and have the …
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 …
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 …
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, …
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 …
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 …
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 …
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.
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 …
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 …
For archiving old data that is infrequently accessed it is perfect. You can choose to let it go into cold/glacier storage which saves even further costs but at the expense of accessibility. I like that you can set access rules to automatically move it to the next storage tier after a certain amount of time that it has not been accessed. I also use it a lot with PHP via the API. We have some custom in-house applications that have a fair amount of data uploaded into them. S3 has been a perfect solution to store these files, taking the load off web servers and never having issues with running out of storage.
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.
Reliable and secure way to store objects in cloud: Storing any type of file(text, pdf, doc, csv, etc) is very easy with S3. Fetching this stored content as and when you require is also pretty easy and can be done using both the console and AWS CLI. Appropriate permissions can be set up for buckets using IAM roles/policies.
Versioning in buckets: S3 gives you a very handy feature to store multiple versions of objects stored in a bucket.
Lifecycle policies: You can set up lifecycle policies in S3 that can move your older objects to IA or Glacier. This setup is very easy and can be done within minutes for a bucket.
Replication: The cross-region replication that S3 provides is wonderful. Beware of the inter-regional data transfer costs though.
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.
The biggest problem is to rename the bucket. There is no direct way to do it. One need to copy entire content to the different bucket with intended bucket name and then remove the old bucket. Sometimes it creates issues.
There is no direct way to upload .zip file and extract it to inside the bucket.
While uploading large files, sometimes you will find a drop of upload speed. I observe it so many times and while checking my internet speed, I find it absolutely perfect. So there must have something wrong on the AWS side.
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.
The UI could have some improvements (better filters) and there is a lack of some useful functionality, such as renaming an existing bucket: the latter is much needed in the context of rapidly evolving companies. Overall though, Amazon S3 (Simple Storage Service) is easy to use and to onboard people and tools to, thanks to its various APIs and flexibility.
It depends on your tier within Amazon on how great of support you get. For us we have a dedicated Point of Contact that is great in taking in what we need and discussing it with the S3 team. The best thing is features we need or suggest have a good chance of landing on their roadmap.
S3 is the most mature simple storage service on the web. It has direct competitors from Google and Azure, as well as a bunch of other competitors that focus on different aspects. For example, Backblaze specializes on file backups, and while s3 can also be used for that, Backblaze provides a better price point in exchange for more focused functionality. S3 really shines in that it performs simple things astonishingly well, while also being flexible enough to stretch itself to other situations (data lakes, file mounts, backup/restores systems, web hosting, etc.).
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.
Allows us to store large amounts of raw traffic from data providers to allow us to view data our systems received at particular times, in order to reconstruct inputs in case of errors
Is capable of storing very large amounts of data cheaply without material impact to our business
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.