Amazon DynamoDB vs. Apache Cassandra

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon DynamoDB
Score 8.9 out of 10
N/A
Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
Cassandra
Score 7.6 out of 10
N/A
Cassandra is a no-SQL database from Apache.N/A
Pricing
Amazon DynamoDBApache Cassandra
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 DynamoDBCassandra
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon DynamoDBApache Cassandra
Considered Both Products
Amazon DynamoDB
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'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
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, …
Chose Amazon DynamoDB
high scalability #single-digit latency. #so much flexile. #very easy to use. # low maintenance.#GLobal Access
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
Amazon DynamoDB is a blind pick if you are already using AWS services suite and your data is also present on the Amazon cloud. If you are not sure of the type of data that you are going to get or you know that is won't always be structured data, then it is also the right choice.
Chose Amazon DynamoDB
The main reason for sticking to DynamoDB is that its part of the AWS suite and since its a managed solution, so we do not have to worry about scalability and reliability. There are some advantages and disadvantages for using DynamoDB and the decision ultimately depends on your …
Chose Amazon DynamoDB
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 …
Chose Amazon DynamoDB
We ended up selecting DynamoDB compared to similar products simply because we host on AWS. To use any other NoSQL solution would require more work in the long run due to having to maintain the EC2 instance, manage updates to the operating system and whatever NoSQL system that …
Chose Amazon DynamoDB
While evaluating Cassandra, PostgreSQL, MongoDB and DynamoDB we found Cassandra and DynamoDB being well suited for us. At the same time we didn't have the luxury of large team or devops so it came down to Amazon DynamoDB. As a small team we are glad to go forward with this …
Chose Amazon DynamoDB
DynamoDB is fully managed which is a great plus over MongoDB. The feature set is not as strong on MongoDB's for document databases, but it the managed aspect is highly compelling. Similarly for Cassandra, DynamoDB is managed. DynamoDB scales much better than CouchDB.
Cassandra
Chose Apache Cassandra
Four years ago, I needed to choose a web-scale database. Having used relational databases for years (PostgreSQL is my favorite), I needed something that could perform well at scale with no downtime. I considered VoltDB for its in-memory speed, but it's limited in scale. I …
Chose Apache Cassandra
DynamoDB is good and is also a truly global database as a service on AWS. However, if your organization is not using AWS, then Cassandra will provide a highly scalable and tuneable, consistent database.
Cassandra is also fault-tolerant and good for replication across multiple …
Chose Apache Cassandra
We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for …
Chose Apache Cassandra
Apache Cassandra has the best of both worlds, it is a Java based NoSQL, linearly scalable, best in class tunable performance across different workloads, fault tolerant, distributed, masterless, time series database. We have used both Apache HBase and MongoDB for some use cases …
Top Pros
Top Cons
Features
Amazon DynamoDBApache Cassandra
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Amazon DynamoDB
9.2
70 Ratings
5% above category average
Apache Cassandra
8.0
5 Ratings
9% below category average
Performance9.269 Ratings8.55 Ratings
Availability9.470 Ratings8.85 Ratings
Concurrency8.868 Ratings7.65 Ratings
Security9.070 Ratings8.05 Ratings
Scalability9.469 Ratings9.55 Ratings
Data model flexibility8.667 Ratings6.75 Ratings
Deployment model flexibility10.023 Ratings7.05 Ratings
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Amazon DynamoDBApache Cassandra
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User Ratings
Amazon DynamoDBApache Cassandra
Likelihood to Recommend
8.9
(80 ratings)
6.0
(16 ratings)
Likelihood to Renew
10.0
(34 ratings)
8.6
(16 ratings)
Usability
8.4
(4 ratings)
7.0
(1 ratings)
Performance
9.1
(44 ratings)
-
(0 ratings)
Support Rating
6.4
(4 ratings)
7.0
(1 ratings)
Implementation Rating
-
(0 ratings)
7.0
(1 ratings)
Product Scalability
9.1
(44 ratings)
-
(0 ratings)
User Testimonials
Amazon DynamoDBApache Cassandra
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
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Apache
Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.
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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.
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Apache
  • Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
  • Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
  • Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
  • Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
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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.
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Apache
  • Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
  • Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
  • There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.
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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.
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Apache
I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
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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.
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Apache
It’s great tool but it can be complicated when it comes administration and maintenance.
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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.
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Apache
No answers on this topic
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.
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Apache
Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.
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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.
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Apache
We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra
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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.
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Apache
No answers on this topic
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.
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Apache
  • I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
  • Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.
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ScreenShots

Amazon DynamoDB Screenshots

Screenshot of Amazon DynamoDB in the AWS Console