Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
RavenDB
Score 8.1 out of 10
N/A
RavenDB is a NoSQL Document Database that is fully transactional (ACID) across the database and throughout clusters. The database minimizes the need for third party addons, tools, or support to boost developer productivity and get projects into production fast. Users can setup and secure a data cluster deploy in the cloud, on-premise or in a hybrid environment. RavenDB offers a Database as a Service solution, allowing users to pass on all…
N/A
Pricing
Amazon DynamoDB
RavenDB
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
RavenDB
Free Trial
No
Yes
Free/Freemium Version
No
Yes
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
RavenDB
Considered Both Products
Amazon DynamoDB
Verified User
Anonymous
Chose Amazon 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.
Other all SQL Databases are based on the traditional Schema Structure and Amazon DynamoDB is NoSQL so you don't need to generate the SQL Schemas. You can store the data whatever you want, whenever you want. You can store data in structured or non-structured any way you want. If …
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 …
MongoDB was basically the first approach we used but because there was concern that some data may miss we were reluctant to use it. Oracle Database and SQL Server was our second approach but it was throttling so in last we tested out Amazon DynamoDB and it met our requirement.
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 …
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.
Amazon DynamoDB supports larger throughput, with better SLA, also, we are considering unstructured data, so Amazon DynamoDB has become the final decision
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 …
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 …
AWS handles hardware provisioning, data recovery, fault tolerance, patching, and database upgrades for DynamoDB since it is a fully managed database service. Businesses can then concentrate on other aspects of their operations, including product development or customer service, …
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.
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 …
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 is slightly different than both the above-stated DBs, with RDS being a relational database and Redshift being a data warehouse used for heavier jobs and analytics and vast data. DynamoDB lies in between both, with it being a no SQL base that can relatively store …
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.
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
First of all, Microsoft Access is also a powerful, efficient, and free database. But the feel of it, I mean the GUI is not all great for me. It is very eye-stressing. MongoDB is also a good database, it too is efficient, productive, and powerful. But, upon this, RavenDB is a …
The team is very nice, very helpful, and answer very fast to any answer you may have. Thanks to their help, we were able to use and understand all the RavenDB features in no time! Documentation for server and client is very clear, with a lot of use cases. Maintenance is easy, …
RavenDB is just smarter than the competitors. The mapping reduction sorting is head and shoulders above everything else I've used. Nothing really approaches comparable in terms of complexity. Because of the searching of predetermined categories, read efficiency is terrible. …
The company needed a cache server that was closest and the most accessible, which is why we are currently experimenting with RavenDB which gives us the option to set up our hub in a local setting.
Much better support, more transparent pricing, much more easy setup process, native integration into c# / net core. We also tried to set up a Mongo Atlas cluster by self-study but weren't able to get this running. There is a much better response when searching in google, but a …
While MongoDB is in general more popular, I cannot fathom why that is. If you want ACID support (and as a developer, you'll always want that), MongoDB is way slower when compared to RavenDB. Furthermore, RavenStudio is just integrated, while
[RavenDB is] just simply much cleverer than the competition. The map reduce indexing is a league above anything else I have used. Nothing else comes close on abstraction as well. Read performance is terrifying due to querying pre calculated indexes. It is just a pity it is not …
Having ACID compliance is a big enough reason to choose RavenDB over the other products. You don't have to worry about losing your data if the plug is pulled. You're able to perform many actions within a transaction and not worry about your data being in a bad state if the …
Installing and configuring. We had some big issues with indexing the data after the documents were created and wanted to expand the index, with millions of records this task mostly did not complete despite a dedicated server.
Out of the many variants of document and SQL databases out there that we have used, RavenDB is our no 1 choice for anything but the smallest projects which can be served with a very small SQL instance. Other than that, RavenDB packs more features and is easier to work with than …
The given alternatives are also powerful and really good noSQL databases but the highest availability of RavenDB allows me/us to know it a lot better. RavenDB is encrypted by default wherever we use it in production and it has a high level of documents compression.
As I have said before in the previous questions ... RavenDB has a very simple clean UI, but stacks up in its power. Though new to me, I have found it to be much easier to learn and use than my previous database - Microsoft SQL Server. RavenDB's simple design and meaningful …
Being that ACID and cluster transaction support is a big plus against all of them. Cool prices on Azure and AWS is another plus. The ability to search between millions of documents.
When I first started using RavenDB, I did evaluate Mongo DB but found it to be lacking. The primary issue was that Mongo DB did not support atomic consistency for the persistence of multiple documents at the same time, although I think this may not be an issue with subsequent …
Once I had got my head around the concept of a document database it was a happy bye-bye to SQL Server. Firebird - far too fiddly - I found myself writing a silly API to sit on top of Firebird just to do the most basic things. MongoDb - in the very short time I spent with it, it …
We chose Raven over Mongo because it has robust support for multi-document transactions, first-class .NET and LINQ support, a well-designed API that has inspired imitation and has better tooling out of the box. We chose Raven over Redis because Raven is a full persistent …
It is useful use-case by use-case. For our use case, it was the best and easiest option for the integration as well as development side. It is serverless so no need of deployment and maintenance hustle. It is easy to scale up due to the same functionality. Supports AWS Security features and just a click away for enabling it so security is good.
RavenDB is very well suited for NoSQL beginners to start easily setting up and using a NoSQL database. Also to set up a high performance and high availability cluster is possible without reading tons of documentation. Very straightforward assistant! The performance is really high.
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.
We've had an excellent experience using RavenDB. Internally we are testing the newer features in 5.0 such as time series, which will effect the con specified previously dependent on the real world performance. We foresee that BattleCrate will continue to use RavenDB as we grow.
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.
Really good .NET client that is very easy to use. The management studio is excellent and puts anything that Microsoft or Oracle have to shame. Very quick to develop with once the complexity hurdle has been overcome. Initially using it can be a bit painful until you fully grasp the event sourced nature of the indexing.
While the actual performance of DynamoDB can vary based on workload and region, it is generally highly responsive and well-regarded for delivering low-latency access to data, making it a strong choice for applications with stringent performance requirements. Organizations often choose DynamoDB for its ability to provide a reliable and performant database service, particularly when combined with effective application design and optimization.
Had a question that was answered in minutes. Never used a NoSQL approach before, but was able to be proficient in a matter of hours. Easy to read API Documentation. 5 out 5 support in book, I have never once ran into an issue that wasn't quickly solved by either their support team or myself doing a quick search online.
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.
RavenDB is just smarter than the competitors. The mapping reduction sorting is head and shoulders above everything else I've used. Nothing really approaches comparable in terms of complexity. Because of the searching of predetermined categories, read efficiency is terrible. RavenDB is a storage system designed for the current websites and functional prototypes. It has an easy-to-use interface and enables quick replication and backup installation. Furthermore, technical assistance responds quickly and walks you through the implementation and deployment procedures.
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.
Businesses may only pay for the services they actually use thanks to DynamoDB's usage-based pricing approach.
AWS handles hardware provisioning, data recovery, fault tolerance, patching, and database upgrades for DynamoDB since it is a fully managed database service.
DynamoDB differs from conventional relational databases in terms of its data model, which might be difficult for developers accustomed to dealing with SQL-based systems.
RavenDB has saved my customers a lot of money with their cloud services' tiered model. The database is able to grow with the project/company and can start out small at a low cost.
RavenDB is free for three nodes and three CPUs, which makes it great for development scenarios. You're able to start rapidly building applications without having to worry about licensing.
Scaling out has allowed us to use three small cloud servers when starting out and get the performance and throughput of a single larger server.