Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
Amazon S3
Score 8.8 out of 10
N/A
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.
N/A
Microsoft Azure
Score 8.4 out of 10
N/A
Microsoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.
$29
per month
Pricing
Amazon DynamoDB
Amazon S3 (Simple Storage Service)
Microsoft Azure
Editions & Modules
Provisioned - Read Operation
$0.00013
capacity unit per hour
Provisioned - Write Operation
$0.00065
capacity unit per hour
Provisioned - Global Tables
$0.000975
per Read Capacity
On-Demand Streams
$0.02
per 100,000 read operations
Provisioned - Streams
$0.02
per 100,000 read operations
On-Demand Data Requests Outside AWS Regions
$0.09
per GB
Provisioned - Data Requests Outside AWS Regions
$0.09
per GB
On-Demand Snapshot
$0.10
per GB per month
Provisioned - Snapshot
$0.10
per GB per month
On-Demand Restoring a Backup
$0.15
per GB
Provisioned - Restoring a Backup
$0.15
per GB
On-Demand Point-in-Time Recovery
$0.20
per GB per month
Provisioned - Point-in-Time Recovery
$0.20
per GB per month
On-Demand Read Operation
$0.25
per million requests
On-Demand Data Stored
$0.25
per GB per month
Provisioned - Data Stored
$0.25
per GB per month
On-Demand - Write Operation
$1.25
per million requests
On-Demand Global Tables
$1.875
per million write operations replicated
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Developer
$29
per month
Standard
$100
per month
Professional Direct
$1000
per month
Basic
Free
per month
Offerings
Pricing Offerings
Amazon DynamoDB
Amazon S3
Microsoft Azure
Free Trial
No
No
Yes
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
—
—
The free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
More Pricing Information
Community Pulse
Amazon DynamoDB
Amazon S3 (Simple Storage Service)
Microsoft Azure
Considered Multiple Products
Amazon DynamoDB
Verified User
Engineer
Chose Amazon DynamoDB
DynamoDB offers strong consistency, more fine-grained control over read and write capacities, and integrates seamlessly with other AWS services. DynamoDB is designed for horizontal scalability and high throughput, making it a better choice for applications with rapidly changing …
Comparing RDS and Dynamo is not fully Apples to Apples comparison. RDS is a more flexible cloud-native solution that supports a wide range of engines that are relational. It is great for running older DB types like Oracle in the Cloud. Because it supports multiple engines, it …
Lesser flexibility but better performance, and more predictable development support are the key points where Amazon DynamoDB comes out on top, when compared to MongoDB.
DynamoDB provided an easy to use, schema-less, out of the box solution that can be used to spin up a full working implementation very easily. It doesn't require extra knowledge such as MongoDB query functions
Dynamo DB is definitely more efficient and able to be configured easier than both. I just would say you have to know what you are doing with SQL as well. Because if you don’t know anything about SQL, you could always use Dynamo DB to help store your big data.
Compared to running your own on-prem SQL infrastructure Amazon Dynamo is easier to set up, faster and more reliable as well as being cheaper in the long run.
We have been preferring DynamoDB over Redis for persistent data. It has a better encryption model and is operationally simpler.
For materialized views we've been using Elasticsearch, but are starting to consider using DynamoDB there too.
We did not use or evaluated any. DynamoDB was our first choice for this particular use case and we were glad we made this choice. Also, knowing the AWS infrastructure and having DynamoDB integrated into the AWS environment helped us greatly with learning DynamoDB and being able …
When you compare database systems it's easy to have an apples to apples comparison. However, when comparing two No-SQL systems it isn't as easy because they are built with different purposes in mind. DynamoDB has been easier to implement because it comes as a Service from …
I wish I could speak more towards this, but I did not take the time to evaluate any other options. As I've mentioned earlier in this review, our entire infrastructure is already inside of AWS - we use dozens of their services - so it was a no brainer for us to keep with that …
As a fully managed NoSQL service, DynamoDB provides a lot of functionality for relatively low cost. Scaling, sharding, throughput performance is managed for you, and you only pay for the bandwidth you provision.
9/10 times I would recommend using MongoDB over DynamoDB. The only real benefit of DynamoDB over MongoDB is that it's already deeply nested in the Amazon ecosystem with tight integration with other AWS tools. Working with Amazons sdks is clunky compared to Mongo, it lacks a …
We evaluated using MongoDB or Amazon DyanmoDB. For us, the biggest advantage is that there's no maintenance cost for Amazon DynamoDB. Mongo gets complicated when you setup sharding. With Amazon DynamoDB, it's literally a push of button to increase throughput. This saves time …
Main advantage of DynamoDB is Amazon's offering as SaaS. This removes the need for managing the database. DynamoDB is well suited for querying simple and flat JSON objects.
Compared to PostgresSQL, I would pick Postgres over Dynamo considering that Postgres is very mature and …
Sql is much more feature rich yet costly and harder to maintain. Requires physical servers while dynamo everything is in the cloud across multiple AZs. Redis is actually great to put on top of dynamo to use as a read cache which is much faster and cheaper, but the storage and …
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 …
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 …
S3 provides an on-demand usage model for storage. You only pay for what you use. Nutanix is an on-premises solution and does not allow for usage-based pricing. Azure was less integrated with our current AWS workloads which helped drive our decision to use s3 with the Amazon …
Amazon S3 comes with all other services of AWS, all other services are very quick and secure with S3 storage, which is the best option for any application. Again, compared to other services like Azure or GCP, AWS provides more configuration and functions to host multi nature …
Prior to using S3, we were hosting all of our assets from the assets pipeline in our Ruby on Rails application. For a small company, this approach was fine but as the assets doubled and tripled, this was no longer the way to go. S3 will help you scale regardless of company …
Some obvious ones are Google storage services like Drive, and their whole arsenal of services. Another could be the Office line where SharePoint and other programs can be used synchronously. I have seen other people use Windows Azure for storage needs similar to ours. We chose …
As most of our work loads and the under laying platforms are build on EMR, Spark and AWS Lambda, we did not find HDFS a suitable solution to have all of our data in. HDFS was very costly as we had to maintain data nodes only for the sole purpose of maintaining the extra storage …
I haven't been personally involved in the decision to use S3, but in comparison to Dropbox or Google Drive, this offers a less robust UI to modify things, while being a cheaper storage mechanism over the rest.
Out of all the other products, I personally feel, S3 is the best! You don't need to worry about the size of the data you store, maintenance is very easy, write a simple lifecycle rule to clear the unwanted and un important data after a certain period of time. No need to have …
Amazon S3 is where you want to default to if you want to store a large amount of data. Compared to formatted data that you can store in Amazon RDS or DynamoDB, you can store your data in any format you want on S3. And the data retention policy can be really useful if you use S3 …
Amazon has had years of development in building their cloud solution. A few other vendors are playing catch up but that's always the case when you have the key to success. The saying goes " if you built it, they will come". :)
Azure provides an environment that while at time is more pricey, the tight integration with our existing Microsoft-based infrastructure makes it difficult to beat.
AWS is competitor and it's leading in cloud space with his wide sprawl of offerings and services. AWS is a ocean once you login you get everything on one console. AWS leads this space with all his offerings and capabilities. But Azure is not behind, it is competing and is …
It’s great for server less and real-time applications. It would be great for gaming and mobile apps. However, if you need relational database and have fixed budget, do not use it. While budget can be managed, you need to be careful. Also this is not a tool for storing big data, there are other wide-column database types you could use for it ins the ad
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.
Azure is particularly well suited for enterprise environments with existing Microsoft investments, those that require robust compliance features, and organizations that need hybrid cloud capabilities that bridge on-premises and cloud infrastructure. In my opinion, Azure is less appropriate for cost-sensitive startups or small businesses without dedicated cloud expertise and scenarios requiring edge computing use cases with limited connectivity. Azure offers comprehensive solutions for most business needs but can feel like there is a higher learning curve than other cloud-based providers, depending on the product and use case.
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.
Microsoft Azure is highly scalable and flexible. You can quickly scale up or down additional resources and computing power.
You have no longer upfront investments for hardware. You only pay for the use of your computing power, storage space, or services.
The uptime that can be achieved and guaranteed is very important for our company. This includes the rapid maintenance for security updates that are mostly carried out by Microsoft.
The wide range of capabilities of services that are possible in Microsoft Azure. You can practically put or create anything in Microsoft Azure.
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
The cost of resources is difficult to determine, technical documentation is frequently out of date, and documentation and mapping capabilities are lacking.
The documentation needs to be improved, and some advanced configuration options require research and experimentation.
Microsoft's licensing scheme is too complex for the average user, and Azure SQL syntax is too different from traditional SQL.
It's core to our business, we couldn't survive without it. We use it to drive everything from FTP logins to processing stories and delivering them to clients. It's reliable and easy to query from all of our pipeline services. Integration with things like AWS Lambda makes it easy to trigger events and run code whenever something changes in the database.
Moving to Azure was and still is an organizational strategy and not simply changing vendors. Our product roadmap revolved around Azure as we are in the business of humanitarian relief and Azure and Microsoft play an important part in quickly and efficiently serving all of the world. Migration and investment in Azure should be considered as an overall strategy of an organization and communicated companywide.
Functionally, DynamoDB has the features needed to use it. The interface is not as easy to use, which impacts its usability. Being familiar with AWS in general is helpful in understanding the interface, however it would be better if the interface more closely aligned with traditional tools for managing datastores.
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.
As Microsoft Azure is [doing a] really good with PaaS. The need of a market is to have [a] combo of PaaS and IaaS. While AWS is making [an] exceptionally well blend of both of them, Azure needs to work more on DevOps and Automation stuff. Apart from that, I would recommend Azure as a great platform for cloud services as scale.
It works very well across all the regions and response time is also very quick due to AWS's internal data transfer. Plus if your product requires HIPPA or some other regulations needs to be followed, you can easily replicate the DB into multiple regions and they manage all by it's own.
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 were running Windows Server and Active Directory, so [Microsoft] Azure was a seamless transition. We ran into a few, if any support issues, however, the availability of Microsoft Azure's support team was more than willing and able to guide us through the process. They even proposed solutions to issues we had not even thought of!
As I have mentioned before the issue with my Oracle Mismatch Version issues that have put a delay on moving one of my platforms will justify my 7 rating.
The only thing that can be compared to DynamoDB from the selected services can be Aurora. It is just that we use Aurora for High-Performance requirements as it can be 6 times faster than normal RDS DB. Both of them have served as well in the required scenario and we are very happy with most of the AWS services.
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.
As I continue to evaluate the "big three" cloud providers for our clients, I make the following distinctions, though this gap continues to close. AWS is more granular, and inherently powerful in the configuration options compared to [Microsoft] Azure. It is a "developer" platform for cloud. However, Azure PowerShell is helping close this gap. Google Cloud is the leading containerization platform, largely thanks to it building kubernetes from the ground up. Azure containerization is getting better at having the same storage/deployment options.
I have taken one point away due to its size limits. In case the application requires queries, it becomes really complicated to read and write data. When it comes to extremely large data sets such as the case in my company, a third-party logistics company, where huge amount of data is generated on a daily basis, even though the scalability is good, it becomes difficult to manage all the data due to limits.
Some developers see DynamoDB and try to fit problems to it, instead of picking the best solution for a given problem. This is true of any newer tool that people are trying to adopt.
It has allowed us to add more scalability to some of our systems.
As with any new technology there was a ramp up/rework phase as we learned best practices.
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.
For about 2 years we didn't have to do anything with our production VMs, the system ran without a hitch, which meant our engineers could focus on features rather than infrastructure.
DNS management was very easy in Azure, which made it easy to upgrade our cluster with zero downtime.
Azure Web UI was easy to work with and navigate, which meant our senior engineers and DevOps team could work with Azure without formal training.