Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
Amazon S3
Score 8.7 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
Pricing
Amazon DynamoDB
Amazon S3 (Simple Storage Service)
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
No answers on this topic
Offerings
Pricing Offerings
Amazon DynamoDB
Amazon S3
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 DynamoDB
Amazon S3 (Simple Storage Service)
Considered Both Products
Amazon DynamoDB
Verified User
Engineer
Chose Amazon DynamoDB
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 …
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 …
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 …
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 …
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.
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.
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'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.
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.
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.
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.
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.