Amazon DynamoDB vs DataStax

Likelihood to Recommend

It is ideal for those projects where you need to store a large amount of data, but you do not know how many will be so you need the database to increase its storage capacity together with the number of users, without having to spend extra money, it also has a great potential thanks to the fast connection it offers, so the data travels at high speed, and this speeds up the performance of the applications, excellent for projects where non-relational databases are used and what matters is to store large quantities of information and use them at high speed.

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Winston Mendes

Software Developer

Globalsoft SolutionsComputer Software, 51-200 employees

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Datastax Cassandra is a Java based linearly scalable NoSQL database, best-in-class tunable performance, fault tolerant, distributed, masterless, time series database and has easy-to-use administration and monitoring functionality with opscenter. Configured correctly there is no downtime and no data loss. The documentation is exhaustive, and the community is agile and supportive, and Datastax provides good support. For all these reasons, Datastax Cassandra has become a NoSQL technology of choice for many platforms.However it has some time investment on infrastructure and regular operational tasks, and if you do not have bandwidth for it, a managed NoSQL solution like DynamoDB might be more appropriate. Also if you have search needs on Cassandra and do not have corresponding Spark/Solr setup, Datastax Cassandra might not be ideal for you.

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Verified User

Professional in Information Technology

Computer Software Company, 5001-10,000 employees

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Feature Rating Comparison

Amazon DynamoDB

DataStax

Performance

Availability

Concurrency

Security

Scalability

Data model flexibility

Deployment model flexibility

Pros

It's very easy to get started, creating a table with a partition/sort key and you're on your way.
You can scale up and down your read/write IO as needed.
You can store structured and unstructured data.
It works great with Web Development as it's JSON based.

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Bob Smith

Founder, Owner

CodeLinguists LLCComputer Software, 1-10 employees

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Scalability: it provides near linear scalability being based on open source Cassandra
Opscenter: it is a powerful and complete tool for monitoring
You can use Spark for analytics workloads

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Verified User

Engineer in Engineering

Financial Services Company, 1001-5000 employees

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Cons

Complex searching (no support for case-insensitive or full-text search).
Only supports up to two-key indexes.
Requires choosing the indexes up-front when doing searches.
Does not have an SQL compatible query front-end.
No join-table support (requires putting all data into one table).

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Chris Moyer

VP of Technology

NewstexComputer Software, 1-10 employees

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Support for aggregation functions is still limited.

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Robert Xu

Director, Database Administration

Connexity, Inc.Internet, 201-500 employees

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Likelihood to Renew

Amazon DynamoDB 9.0

Based on 31 answers

We will most likely continue to use DynamoDB for certain use-cases. If we stopped using DynamoDB as often, it would likely be because we started using Aurora Serverless more. Aurora Serverless may offer similar availability, management and cost benefits while allowing developers to use their MySQL tools and experience.

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Verified User

Engineer in Engineering

Research Company, 11-50 employees

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DataStax 7.7

Based on 3 answers

Based on my experience with Datastax Cassandra.

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Verified User

Professional in Information Technology

Computer Software Company, 5001-10,000 employees

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Alternatives Considered

We evaluated using MongoDB or Amazon DyanmoDB. For us, the biggest advantage is that there's no maintenance cost for Amazon DynamoDB. Mongo gets complicated when you setup sharding. With Amazon DynamoDB, it's literally a push of button to increase throughput. This saves time and money on DevOps resources.

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Verified User

Engineer in Engineering

Computer Software Company, 11-50 employees

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We chose datastax because we need a system always available and capable of ingesting a large amount of data per second, even if eventually consistent and with multi data center sync native support.We considered Cloudera as an alternative using Kafka as the ingestion layer but we were not completely satisfied with the multi data center support.

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Verified User

Engineer in Engineering

Financial Services Company, 1001-5000 employees

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Return on Investment

Since the Amazon manages the instance, the amount of time a developer needs to spend configuring the database is less. For comparison, if we were to manage the same instance manually, we need to set up EC2 instance, install the DB, setup backup scripts, track backup failures, which is a great overhead for the dev. Using DynamoDB this overhead is reduced and hence having a great ROI.
Great documentation and easy setup makes an easy learning curve to transition to DynamoDB. Only caveat is as with any database, the data structure should be thoroughly analyzed for types of querying because there are limitations with the DynamoDB API.
Ties very well with rest of the Amazon eco system. Having rest of the applications in Amazon allows managing the application security a breeze.

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