What users are saying about

Amazon DynamoDB

Top Rated
52 Ratings

Cassandra

Top Rated
61 Ratings

Amazon DynamoDB

Top Rated
52 Ratings
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Score 8.2 out of 101

Cassandra

Top Rated
61 Ratings
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Score 8.2 out of 101

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Likelihood to Recommend

Amazon DynamoDB

If you start with Amazon DynamoDB, you are over optimizing for the future. In my opinion, use Amazon DynamoDB only when SQL can not handle the load of your application.
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Cassandra

Cassandra excels in a broad range of applications -- especially if you understand its data model and write your applications accordingly. It's an excellent choice for time-series data, and a poor choice for application queues. It performs the best if you can simply record history and compute from it, rather than going back and editing or deleting things a lot.
David Prinzing profile photo

Feature Rating Comparison

NoSQL Databases

Amazon DynamoDB
7.9
Cassandra
Performance
Amazon DynamoDB
8.0
Cassandra
Availability
Amazon DynamoDB
8.4
Cassandra
Concurrency
Amazon DynamoDB
9.0
Cassandra
Security
Amazon DynamoDB
8.7
Cassandra
Scalability
Amazon DynamoDB
9.7
Cassandra
Data model flexibility
Amazon DynamoDB
4.0
Cassandra
Deployment model flexibility
Amazon DynamoDB
7.3
Cassandra

Pros

  • Amazon DynamoDB is infinitely scalable. It is fast and Amazon automatically allocates more resources.
  • No predefined schema is required. This ensures flexibility.
  • Minimum administrative cost since Amazon manages all that. This works for small companies since you don't need a DevOps headcount.
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  • 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.
David Prinzing profile photo

Cons

  • Query "language" leaves much to be desired. If you're coming from a database like MongoDB or SQL you'll find it extremely difficult to get data back out of the system without breaking the bank.
  • Because querying is poor, often the only way to get data out of arbitrary fields is by scanning the records – but the pricing model for this is cost prohibitive. This means you frequently need additional architecture to keep track of where data is stored in the hash table. While this is an issue for lots of NoSQL database, DynamoDB is probably the worst offender I've used to date because of the pricing model.
  • Amazon does offer a local version of DynamoDB you can run in development, but its an extremely clunky and very hard to integrate into any kind of continuous integration.
Justin Schroeder profile photo
  • 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 DynamoDB6.9
Based on 13 answers
As I said earlier, DynamoDB works well for our application. There's a few shortcoming but there's workarounds for almost everything.
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Cassandra8.0
Based on 11 answers
In our POC Cassandra satisfies all our needs and expectations. We would like to do an additional POC to test its cross-continent cluster level replication features, measuring the performance and data consistency level to help us finally decide how to move to production.
yixiang Shan profile photo

Alternatives Considered

9/10 times I would recommend using MongoDB over DynamoDB. The only real benefit of DynamoDB over MongoDB is that it's already deeply nested in the Amazon ecosystem with tight integration with other AWS tools. Working with Amazons sdks is clunky compared to Mongo, it lacks a truly expressive query language, and the pricing makes your data inflexible.
Justin Schroeder profile photo
Cassandra is the only NoSQL database I have extensive experience with. In terms of other open source database solutions, I can say that I like Cassandra as much or equally as traditional Oracle MySQL, and a lot more than PostgresSQL. The decision to use Cassandra was driven by the ability for fast read and writes, as well as fault tolerance by having multiple rings in a cluster which shard data to each other in near real time.
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Return on Investment

  • We were able to achieve our goal using Amazon – store every single email our system that has ever been sent in fluid database for long term recover without significantly impacting query times at scale.
  • We have been unable to effectively add additional features using the data set because of the pricing structure and incurred cost involved with performing repeated scans over the dataset.
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  • Cassandra has had a positive effect on our ROI by improving uptime and performance
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Pricing Details

Amazon DynamoDB

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Cassandra

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details