Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon DynamoDB
Score 8.2 out of 10
N/A
Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
MongoDB
Score 8.9 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
SingleStore
Score 7.8 out of 10
N/A
SingleStore aims to enable organizations to scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.
$0.69
per hour
Pricing
Amazon DynamoDBMongoDBSingleStore
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
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
OnDemand
$0.69
per hour
Offerings
Pricing Offerings
Amazon DynamoDBMongoDBSingleStore
Free Trial
NoYesYes
Free/Freemium Version
NoYesYes
Premium Consulting/Integration Services
NoNoYes
Entry-level Setup FeeNo setup feeNo setup feeOptional
Additional DetailsFully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
Amazon DynamoDBMongoDBSingleStore
Considered Multiple Products
Amazon DynamoDB
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
Chose Amazon DynamoDB
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 …
Chose Amazon DynamoDB
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
Chose Amazon DynamoDB
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.
Chose Amazon DynamoDB
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 …
Chose Amazon DynamoDB
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…
Chose Amazon DynamoDB
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.
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.
Chose Amazon DynamoDB
i think both depends on usuability and app requirement
Chose Amazon DynamoDB
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 …
Chose Amazon DynamoDB
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 …
Chose Amazon DynamoDB
Compare to other products its so easier to set up, meeting all of our business requirements and easy usable, highly efficient and scalable.
Chose Amazon DynamoDB
high scalability #single-digit latency. #so much flexile. #very easy to use. # low maintenance.#GLobal Access
Chose Amazon DynamoDB
Amazon DynamoDB seems to be more cost effective and easy to integrate with other aws services.
Chose Amazon DynamoDB
Haven't had a chance to use this up to an extent to be compared to DynamoDB.
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 …
Chose Amazon DynamoDB
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.
Chose Amazon DynamoDB
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
Chose Amazon DynamoDB
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 …
Chose Amazon DynamoDB
Because of it's access control features, quick scalability and high performance.
MongoDB
Chose MongoDB
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 …
Chose MongoDB
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 …
Chose MongoDB
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 …
Chose MongoDB
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 …
Chose MongoDB
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 …
Chose MongoDB
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.
SingleStore
Chose SingleStore
SingleStore provides a solution for working with larger amount of data (vs. MySQL) with better performance (vs. BigQuery) without having to preprocess the data (vs. MongoDB), so basically it does better for specific use cases.
Chose SingleStore
We knew early on that MySQL (Amazon Aurora) would not be suitable for this workload as it cannot query our time series data as fast as SingleStore. We also use MongoDB Atlas for another application but we could not achieve the raw speed we saw from SingleStore. Our technical …
Chose SingleStore
SingleStore outperformed both MongoDB and PostgreSQL for OLAP workloads. Its ability to shard data and handle parallel processing of SQL "JOIN" queries across shards is a game changer.
Chose SingleStore
SingleStore outperforms Snowflake in real-time analytics and transactional workloads but lags in large-scale batch processing. Compared to MongoDB Atlas, SingleStore excels in complex SQL queries and joins, while MongoDB handles unstructured, document-based data better. Its …
Chose SingleStore
SingleStore (memsql) out performs based on our analysis with sample data sets within org. We could see limitations with other products which SingleStore can overcall like scaling with data while performing with similar SLA. It also has the advantage of row store and column …
Chose SingleStore
Greenplum is good in handling very large amount of data. Concurrency in Greenplum was a major problem. Features available in SingleStore like Pipelines and in memory features are not available in Greenplum.

Gemfire was not scaling well like SingleStore. Support of both …
Chose SingleStore
DynamoDB was fast but no ability to do OLAP queries

Aurora couldn't handle our data scale at all
Chose SingleStore
Its easier to query and faster. Ingestion is for the most part easier to understand and monitor and directly integrated with other storage solution products we use such as AWS S3. Singlestore overall is a better database to serve up an application large amounts of data very …
Chose SingleStore
SingleStore provides an abstraction layer in managing a sharded database solution reducing complexity for the FLOWD team. Coupled with the SingleStore Managed Service, we are partnering with SingleStore to provide FLOWD services to various utilities & councils.
Chose SingleStore
SingleStore was the fastest sql database we have tried, allowing for analytical queries on TBs of data.
Chose SingleStore
We've tried both these above, to solve ingestion and analytical queries. Dynamo was a perfect ingestion service, but it didn't allow us to run intense analytical queries. Aurora helped us run these analytical queries, and ingestion was reasonable, BUT the queries were simply …
Chose SingleStore
SingleStore is simply easier to use and most importantly much, much faster. For Big Data, it is an absolute life saver :)
Chose SingleStore
We selected SingleStore due to its multi cloud nature, SQL compatibility and customer references who operate similar applications as us
Chose SingleStore
It seems that SingleStore is good at being able to handle complex queries against large datasets out of the box. In the past, we've had to do quite a bit of manual configuration and database performance tuning, but SingleStore (so far) has seemed to require minimal …
Chose SingleStore
It does the same but in the same platform. [SingleStore (formerly MemSQL)] can replace most of the use cases those other technologies solve.
Chose SingleStore
I guess the main difference is how the memory is used for stacking and storing data until it reaches the final destination, the performance is awesome compared with others and when you have a real time business with a certain complexity. The development team would be more …
Features
Amazon DynamoDBMongoDBSingleStore
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Amazon DynamoDB
9.2
69 Ratings
3% above category average
MongoDB
10.0
39 Ratings
12% above category average
SingleStore
-
Ratings
Performance9.368 Ratings10.039 Ratings00 Ratings
Availability9.569 Ratings10.039 Ratings00 Ratings
Concurrency9.067 Ratings10.039 Ratings00 Ratings
Security9.269 Ratings10.039 Ratings00 Ratings
Scalability9.468 Ratings10.039 Ratings00 Ratings
Data model flexibility8.266 Ratings10.039 Ratings00 Ratings
Deployment model flexibility10.023 Ratings10.038 Ratings00 Ratings
Relational Databases
Comparison of Relational Databases features of Product A and Product B
Amazon DynamoDB
-
Ratings
MongoDB
-
Ratings
SingleStore
6.9
3 Ratings
14% below category average
ACID compliance00 Ratings00 Ratings5.93 Ratings
Database monitoring00 Ratings00 Ratings7.43 Ratings
Database locking00 Ratings00 Ratings6.63 Ratings
Encryption00 Ratings00 Ratings7.43 Ratings
Disaster recovery00 Ratings00 Ratings5.93 Ratings
Flexible deployment00 Ratings00 Ratings7.73 Ratings
Multiple datatypes00 Ratings00 Ratings7.43 Ratings
Best Alternatives
Amazon DynamoDBMongoDBSingleStore
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
InterSystems IRIS
InterSystems IRIS
Score 8.0 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
InterSystems IRIS
InterSystems IRIS
Score 8.0 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
SAP IQ
SAP IQ
Score 10.0 out of 10
All AlternativesView all alternativesView all alternativesView all alternatives
User Ratings
Amazon DynamoDBMongoDBSingleStore
Likelihood to Recommend
8.9
(79 ratings)
10.0
(79 ratings)
7.8
(73 ratings)
Likelihood to Renew
10.0
(34 ratings)
10.0
(67 ratings)
8.2
(5 ratings)
Usability
9.1
(4 ratings)
10.0
(15 ratings)
8.2
(8 ratings)
Availability
-
(0 ratings)
9.0
(1 ratings)
9.1
(2 ratings)
Performance
9.1
(42 ratings)
-
(0 ratings)
8.3
(47 ratings)
Support Rating
5.2
(4 ratings)
9.6
(13 ratings)
8.3
(9 ratings)
Online Training
-
(0 ratings)
-
(0 ratings)
7.3
(1 ratings)
Implementation Rating
-
(0 ratings)
8.4
(2 ratings)
7.3
(2 ratings)
Ease of integration
-
(0 ratings)
-
(0 ratings)
9.1
(1 ratings)
Product Scalability
9.1
(42 ratings)
-
(0 ratings)
8.2
(2 ratings)
Vendor post-sale
-
(0 ratings)
-
(0 ratings)
8.2
(2 ratings)
Vendor pre-sale
-
(0 ratings)
-
(0 ratings)
8.2
(2 ratings)
User Testimonials
Amazon DynamoDBMongoDBSingleStore
Likelihood to Recommend
Amazon AWS
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
Read full review
MongoDB
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.
Read full review
SingleStore
Good for Applications needing instant insights on large, streaming datasets. Applications processing continuous data streams with low latency. When a multi-cloud, high-availability database is required When NOT to Use Small-scale applications with limited budgets Projects that do not require real-time analytics or distributed scaling Teams without experience in distributed databases and HTAP architectures.
Read full review
Pros
Amazon AWS
  • To manage varying workloads, it enables users to increase capacity as necessary and decrease it as needed.
  • Users can take advantage of its auto-scaling, in-memory caching, and backup without paying for the services of a database administrator.
  • We can use it for low scale operations.
Read full review
MongoDB
  • 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.
Read full review
SingleStore
  • Technical support is stellar -- far above and beyond anything I've experienced with any other company.
  • When we compared SingleStore to other databases two years ago, we found SingleStore performance to be far superior.
  • Pipeline data ingestion is exceptionally fast.
  • The ability to combine transactional and analytical workloads without compromising performance is very impressive.
Read full review
Cons
Amazon AWS
  • Cost model may not be easy to control and may lead to higher costs if not carefully planned
  • Indexing may be a cost culprit when not planned, because it's not included on the data costs
  • The Query Language may not fulfill everybody's expectations, as it has less features than those of competitors.
Read full review
MongoDB
  • 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.
Read full review
SingleStore
  • It does not release a patch to have back porting; it just releases a new version and stops support; it's difficult to keep up to that pace.
  • Support engineers lack expertise, but they seem to be improving organically.
  • Lacks enterprise CDC capability: Change data capture (CDC) is a process that tracks and records changes made to data in a database and then delivers those changes to other systems in real time.
  • For enterprise-level backup & restore capability, we had to implement our model via Velero snapshot backup.
Read full review
Likelihood to Renew
Amazon AWS
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.
Read full review
MongoDB
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.
Read full review
SingleStore
We haven't seen a faster relation database. Period. Which is why we are super happy customers and will for sure renew our license.
Read full review
Usability
Amazon AWS
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.
Read full review
MongoDB
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.
Read full review
SingleStore
[Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
Read full review
Reliability and Availability
Amazon AWS
No answers on this topic
MongoDB
No answers on this topic
SingleStore
Solutions are based around a business needs and even when implementing such solution, real time insights are also followed through showing the updates the business are implementing while informing the end users as what is new with technology.
Read full review
Performance
Amazon AWS
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.
Read full review
MongoDB
No answers on this topic
SingleStore
SingleStore excels in real-time analytics and low-latency transactions, making it ideal for operational analytics and mixed workloads. Snowflake shines in batch analytics and data warehousing with strong scalability for large datasets. SingleStore offers faster data ingestion and query execution for real-time use cases, while Snowflake is better for complex analytical queries on historical data.
Read full review
Support Rating
Amazon AWS
I have not had to contact support for this service, however I have had to contact AWS for other services and their support has been good.
Read full review
MongoDB
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.
Read full review
SingleStore
The support deep dives into our most complexed queries and bizarre issues that sometimes only we get comparing to other clients. Our special workload (thousands of Kafka pipelines + high concurrency of queries). The response match to the priority of the request, P1 gets immediate return call. Missing features are treated, they become a client request and being added to the roadmap after internal consideration on all client needs and priority. Bugs are patched quite fast, depends on the impact and feasible temporary workarounds. There is no issue that we haven't got a proper answer, resolution or reasoning
Read full review
Online Training
Amazon AWS
No answers on this topic
MongoDB
No answers on this topic
SingleStore
Would prefer in person training but for online training, it's almost as good as in person
Read full review
Implementation Rating
Amazon AWS
No answers on this topic
MongoDB
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.
Read full review
SingleStore
We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
Read full review
Alternatives Considered
Amazon AWS
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.
Read full review
MongoDB
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.
Read full review
SingleStore
Greenplum is good in handling very large amount of data. Concurrency in Greenplum was a major problem. Features available in SingleStore like Pipelines and in memory features are not available in Greenplum. Gemfire was not scaling well like SingleStore. Support of both Greenplum and Gemfire was not good. Product team did not help us much like the ones in SingleStore who helped us getting started on our first cluster very fast.
Read full review
Scalability
Amazon AWS
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.
Read full review
MongoDB
No answers on this topic
SingleStore
Very reliable. Coming from mariadb, singlestore has made our application more reliable and faster!
Read full review
Return on Investment
Amazon AWS
  • 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.
Read full review
MongoDB
  • 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
Read full review
SingleStore
  • As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data.
  • Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog.
Read full review
ScreenShots

Amazon DynamoDB Screenshots

Screenshot of Amazon DynamoDB in the AWS Console

MongoDB Screenshots

Screenshot of Screenshot of Screenshot of Screenshot of Screenshot of Screenshot of