Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
MariaDB Platform
Score 9.5 out of 10
N/A
MariaDB is an open-source relational database made by the original developers of MySQL, supported by the MariaDB Foundation and a community of developers. The community states recent additional capabilities as including clustering with Galera Cluster 4, compatibility with Oracle Database, and Temporal Data Tables, allowing one to query the data as it stood at any point in the past.
N/A
MongoDB
Score 8.8 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
Amazon DynamoDB
MariaDB Platform
MongoDB
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
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Amazon DynamoDB
MariaDB Platform
MongoDB
Free Trial
No
Yes
Yes
Free/Freemium Version
No
Yes
Yes
Premium Consulting/Integration Services
No
Yes
No
Entry-level Setup Fee
No setup fee
Optional
No setup fee
Additional Details
—
—
Fully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
Amazon DynamoDB
MariaDB Platform
MongoDB
Considered Multiple Products
Amazon DynamoDB
Verified User
Director
Chose Amazon DynamoDB
More flexible and easier to get started with than RDS, but, in my opinion, much worse monitoring/cost and query/modeling complexity than MongoDB
MongoDB vs. Amazon DynamoDB:• MongoDB requires more human management than DynamoDB, which is a fully managed service.• DynamoDB's scalability is automatic, whereas MongoDB's horizontal scaling may require more work.• When compared to DynamoDB, MongoDB offers more extensive data …
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
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.
We are always assembling our solutions on AWS and DynamoDB is a better fit for us because of its simplicity. DynamoDB has its ow sets of triggers that make this an integrated solution on AWS. Besides, we wanted to use a key-value solution for our simple edge DB, and we didn't …
DynamoDB's scalability is more automated and effortless, making it easier to handle rapid growth. Other tools require more manual configuration while DynamoDB simplifies database administration. Also, DynamoDB provides strong consistency while other tools like MongoDB and Apache…
MongoDB has some performance issues and can get corrupted from time to time and has needed to be rebuilt. We have not had that experience while using DynamoDB.
For our use case, we needed a noSQL that would work with AWS Lambdas of specific parts of the internal web applications. We optimized billing and uses , diversified databases for various parts; so it’s not very expensive.
Verified User
Engineer
Chose Amazon DynamoDB
i think both depends on usuability and app requirement
Performance at high scales is better and the cost at high scales is less. If one has a ton of data generated and has to work their way through it, I think Amazon DynamoDB should the go-to database. There are no compromises when it comes to performance at a huge scale. With any …
The Amazon Web Services managed Amazon DynamoDB has excellent features which makes it stand out from all the others in market right now. The management ease it offers is far superior than its competitors and on top of that the on-demand pricing model is an advantage which works …
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 …
The automation is much more subtle and it performs way better for internet-scale applications. No matter the number of connections, the performance doesn't dip even a bit.
Mongo services are outside of our Vpc and are on a different network. Since most of our infra is on AWS, dynamo by AWS was a natural choice. Most of our engineers are familiar with AWS sdk and the console so that brought in a much smaller learning curve for our engineering team
It seamlessly integrates with Lambda, simplifying the deployment and management of serverless architecture. Both Lambda and DynamoDB are designed are highly scalable. Lambda functions can be triggered by various AWS services and events, such as changes in DynamoDB tables which …
Thanks to MySQL compatibility, everything you've learned while using it can be utilized when using MariaDB. Therefore it's a better choice than MongoDB and MSSQL if you're looking to switch away from MySQL. MariaDB is also a very mature and stable product, unlike MongoDB that …
MariaDB is perhaps the best open source database server available, combining a wide range of supported platforms, MySQL compatibility, a low footprint, and reasonably high performance. If you have cost constraints, or limited server resources, I recommend MariaDB, particularly …
MariaDB provided the best fit for our business in upgrading legacy systems which were originally designed to use MySQL as a backend. By using MariaDB, no changes to the overall systems needed to be altered, reducing the time needed to upgrade everything. Other solutions …
We migrated away from MySQL because of stability issues; when choosing a new database system we considered FirebirdSQL (having some experience from other projects) and did not use it because of stability and lack of standard SQL features in its query language; and Amazon's …
MySQL is a great for querying related data, but it's unable to store structured data and has a fixed schema. Also SQL can be non-intuitive. DynamoDB, CouchDB and Redis all make querying the data quite difficult and lack important features. The problem CouchDB tries to solve is …
In our early development days we weighed NoSQL databases like MongoDB with RDBMS solutions like MySQL. We were more familiar with MySQL from past experience but also were wary of painful data migrations that slowed down development iterations and increased the risk of outages …
Your default choice should not be MongoDB in my opinion. Most user-facing systems are relational by nature so a well known and reliable SQL database would be easier to maintain and simpler to develop long term. If you highly value speed of development go with Firebase. If you …
It does not belong to certain cloud platforms. MongoDB is an independent program that works with any cloud platform including Amazon Web Services and the Google Cloud Platform. For companies who want to maintain a cloud agnostic structure, MongoDB is a great choice for NoSQL …
We tend to choose MongoDB when we're faced with a particular situation: we know that we need a NoSQL database in general, and want an open-source implementation that allows us to prevent against platform lock-in. Amazon's new DocumentDB product even allows us to choose to use …
MongoDB is the most complete database of NoSQL type. In my opinion, it has all the tools for a good development of a database. I have not had problems when using the application.
MongoDB was the most full-featured NoSQL database we evaluated - that offered atomic transactions at a document level, built-in HA & DR, open source, robust queries, and enterprise level support.
Other platforms had specific parts of what we were looking for - MongoDB had it all.
Features
Amazon DynamoDB
MariaDB Platform
MongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
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
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
Simpler learning curve. MariaDB is a cleaner, simpler system that is (IMO) easier to learn and easier to manage effectively than many other database systems.
Lower hardware requirements. After migrating to MariaDB from another database software system, we find that our hardware needs have substantially decreased.
MariaDB support is very responsive. It's like they actually care. On the few occasions we've run into technical issues, support has always come through with what we needed. Once it was showing me a relatively new feature the server supported that I wasn't aware of, that, once I was able to properly make use of it helped me resolve a serious production performance issue.
Architectural flexibility. As an example, the ready availability of synchronous (Galera) versus asynchronous replication schemes without being locked into one of the other by enormous technical complexity or punitive licensing, allows the customer to find what really works best for their needs.
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
Driver Support - Some third party applications use database drivers that cause unexplained slowness with MariaDB. This can be worked around by using the MySQL drivers, but it's not clear what causes the problem in the first place.
Support - While online communities are helpful in diagnosing problems, there isn't as much professional documentation/support available for MariaDB as some of the other major database options.
Data Visualization - It would be helpful if there were more built in options for analyzing statistics and generating reports.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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.
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
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.
MariaDB is very usable and stable to be used in production settings as an alternative to MySQL. The shortcomings of SQL are present but well understood in the community, and if the decision were to be made again, I would choose MariaDB over MySQL on future projects.
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
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.
We have launched several inquiries to MariaDB support and they have always responded very quickly and have not been tutoring for the duration of the incident/problem.
Likewise, they want to hold constant meetings with the client to get their opinion as well as how they can help.
I see a very human support and concerned about the customer.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
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.
MariaDB stacks up the the competition just fine. Due to is ture open source nature we do not have to worry about licencing and spending money on nothing. Moreover, MariaDB does everything that we need to get done. We can run data that is a million rows or many smaller projects on the same environment with little overhead. One of the best features that MariaDB has is the ability of backup or dump data to standard text sql statements. That was one of the reasons why we choose MariaDb because it makes backups or transferring data a snap
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
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.
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB