Amazon DynamoDB vs DataStax

Amazon DynamoDB

DynamoDB is great for two cases. The first is for services that do not experience high loads or demand high availability. DynamoDB is inexpensive, and it provides great developer velocity. The second is for applications that demand high performance, have well-understood requirements, and a narrow range of queries.

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Engineer in Engineering

Research Company, 11-50 employees

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DataStax

The best scenarios where to use it are when you need a really high write rate and you know the queries you are going to execute in advance. If you don't know how you will access the data in advance it is better to look at other solutions.

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Engineer in Engineering

Financial Services Company, 1001-5000 employees

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Feature Rating Comparison

Amazon DynamoDB

7.9

DataStax

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Performance

8.0

—

Availability

8.4

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Concurrency

9.0

—

Security

8.7

—

Scalability

9.7

—

Data model flexibility

4.0

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Deployment model flexibility

7.3

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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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Computer Software Company, 11-50 employees

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Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.

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Professional in Information Technology

Computer Software Company, 5001-10,000 employees

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Cons

It's a NoSQL database. That means you lose all the capabilities of a traditional RDBMS model. You can't do joins to query data and you lose ACID properties.
DynamoDB does not support multiple indices. That means for certain queries, you need to do full table scans which is not desirable. There are work arounds for this.
The provisioned throughput doesn't degrade gracefully. That means that once you hit the limit, the requests are denied. It's tricky to come up with the limits of your application.

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Computer Software Company, 11-50 employees

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The move from SQL to NoSQL paradigm is always difficult for people who have been using SQL for most part of their technical lives. Even if NoSQL has better performance and is more scalable, the database interface/functionality needs to be seamless for users. This has always been the top challenge. Now with the advent of ACID and horizontally scaling Google Spanner, the competition is rife for what a database can provide.
Though one can be immediately productive, if you get corner cases in your usage with Datastax Cassandra, you have to really know it better. There is a learning curve. Understanding Cassandra server logs, audit logs and sstables helps.
Debugging can be longer especially if you hit corner cases, like not using Light Weight transaction correctly, timestamp ties or getting RuntimeException on scrub/repair/compaction (java.lang.RuntimeException: 30623431613136352d656433372d343939322d393066342d366632313961393530353062 is not defined as a collection) and such.
Datastax Cassandra has great benefits in product, and features but there are costs on infrastructure maintenance and regular operational tasks. Not that there is any technical component that can self heal :-), but this time investment in Datastax Cassandra is more compared to SQL db, say MySQL.

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Likelihood to Renew

Amazon DynamoDB7.1

Based on 13 answers

We started with DynamoDB for few of the applications that I built as its a pragmatic solution. But as our data started to evolve, we started to hit limitations of the DynamoDB's querying and it gets increasingly frustrating to write code around the DynamoDB's limitations that I mentioned earlier. This caused us to switch from DynamoDB to Postgres in both the cases where we mixed the traditional SQL with NoSQL data.

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Anudeep Palanki

Application Developer

Monsanto CompanyFarming, 10,001+ employees

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DataStax7.6

Based on 3 answers

We will continue to use it because it scales well with commodity hardware and we are satisfied with the documentation and support.

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Engineer in Engineering

Financial Services Company, 1001-5000 employees

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Alternatives Considered

Sql is much more feature rich yet costly and harder to maintain. Requires physical servers while dynamo everything is in the cloud across multiple AZs. Redis is actually great to put on top of dynamo to use as a read cache which is much faster and cheaper, but the storage and retrieval options are not as robust and the reliability is decreased

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Adam Lauer

Software Engineer

Earth NetworksEnvironmental Services, 51-200 employees

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Amazon DynamoDB and Datastax Cassandra are similar on masterless architecture and principles, DynamoDB is managed and needs cost analysis. If you need to have better control, Datastax is better.I also did a prototype with Google Spanner in one of the recent innovation days, it provides the best of both worlds but being a service on Google Cloud Platform(GCP) works if your services are primarily on GCP. Amazon Aurora is a relational database with higher performance and is a good candidate if search and default relational behavior is preferred.For now, Datastax worked well for us as it provides best in class performance across different kinds of read/write/mixed workloads. It provides linear scalability which works for the best performance, lowest latency and highest throughput. If configured correctly, there is no downtime and no data loss.

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Computer Software Company, 5001-10,000 employees

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