Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
Riak
Score 10.0 out of 10
N/A
Riak is a NoSQL database from Basho Technologies in Bellevue, Washington.
N/A
Pricing
Amazon DynamoDB
Riak
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
Riak
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
Riak
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 …
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 …
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
MongoDB seems to have copied a lot of functionality from Riak. This may be because MongoDB hired a number of former Basho engineers when Basho went bankrupt. That said, the new functions added to Riak after it became open source have successfully differentiated itself from …
Every database has positives and negatives. Redis is very good at set operations, but not as good at executing fast queries. MongoDB is a much cheaper data store than Riak, but not as highly available and scalable. Searching Riak is also faster than searching MongoDB or …
Because of the RESTful HTTP interface, the consistency model, and because of the catalog-driven data model, Riak was an easy win over Redis and Memcached.
At the time I worked on the project those were the three competing technologies I evaluated. Couchbase didn't have memcache integrated at the time. Riak was by far the easiest to set up, and it's linking capability struck the right balance of having just enough relational …
Riak is a key/value pair store which is great for certain use cases. For our use case, the ability to search is an extremely useful feature. Apache Cassandra can provide this while Riak cannot. Also again for our use case, the ability to delete is critical as we strive to …
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.
Riak is very good if you need a resilient data store that can handle large amounts of documents very fast. If you have 1,000,000 documents and need to execute complex queries, it is great. Riak's SOLR engine is fast, however if you have extremely high amount of queries in a very limited time range, it can fail in a bad way.
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.
Riak works great for our use case but the fact that deletes seem to resurrect is a real issue for us. Unless we can get this solved, we'll continue to look at other products to see if our use case fits. Otherwise Riak is a great product and it fits our use case 95%. We have found work arounds to the remaining 5%.
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.
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.
Despite Basho going bankrupt and the project becoming fully open-source, community support is reasonably good, albeit a little slow at times. Paid enterprise-grade support is also available from former Basho engineers but the same company also contributes to the community support for free for basic questions or specific knowledge areas.
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.
MongoDB seems to have copied a lot of functionality from Riak. This may be because MongoDB hired a number of former Basho engineers when Basho went bankrupt. That said, the new functions added to Riak after it became open source have successfully differentiated itself from MongoDB.
Amazon S3 is a nice tool but when you are at significant scale with regionally specific data (joys of GDPR), it's much easier to keep it in house and Riak CS lets you do exactly that. All you need to do is point your application at Riak CS instead of Amazon S3 and it just works as if nothing has changed.
When we evaluated against Cassandra, we found the tools available did not match our needs at the time.
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.