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Top Rated
86 Ratings
8 Ratings

Amazon DynamoDB

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Top Rated
86 Ratings
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Score 8.5 out of 101
8 Ratings
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Score 7.4 out of 101

Likelihood to Recommend

Amazon DynamoDB

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.
Winston Mendes profile photo

MemSQL

MemSQL is especially useful to serve as a back-end storage for spark streaming, and also small update problems. The streamliner technology is very helpful to process daily streaming data and consequent data analysis. Same SQL syntax is also very handy for people to learn and use.
Sachin Aggarwal profile photo

Feature Rating Comparison

NoSQL Databases

Amazon DynamoDB
8.6
MemSQL
Performance
Amazon DynamoDB
9.0
MemSQL
Availability
Amazon DynamoDB
9.3
MemSQL
Concurrency
Amazon DynamoDB
9.0
MemSQL
Security
Amazon DynamoDB
9.3
MemSQL
Scalability
Amazon DynamoDB
9.5
MemSQL
Data model flexibility
Amazon DynamoDB
6.7
MemSQL
Deployment model flexibility
Amazon DynamoDB
7.3
MemSQL

Pros

Amazon DynamoDB

  • 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.
Bob Smith profile photo

MemSQL

  • Faster query speed than traditional SQL database.
  • It con server in the pipeline to deal with streaming data with Kafka, spark streaming and MemSQL
  • It is very scalable.
Tianwen Chu profile photo

Cons

Amazon DynamoDB

  • 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).
Chris Moyer profile photo

MemSQL

  • Provide faster python API for invoking MemSQL
  • MemSQL connection between spark failed when more than around 48 partitions data processing
  • Better tuning of MemSQL performance on Scale-up server
Sachin Aggarwal profile photo

Likelihood to Renew

Amazon DynamoDB

Amazon DynamoDB 8.8
Based on 28 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.
No photo available

MemSQL

MemSQL 5.0
Based on 1 answer
I still want to see the performance about using latest version of spark and memsql. About renewal, if there is a new and better version of spark-memsql connector, then maybe.
Tianwen Chu profile photo

Alternatives Considered

Amazon DynamoDB

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.
No photo available

MemSQL

I have tried using CSV as a back-end storage, yet I/O is very heavy, direct transit from spark to MemSQL in memory really beats.
Sachin Aggarwal profile photo

Return on Investment

Amazon DynamoDB

  • 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.
Anudeep Palanki profile photo

MemSQL

  • It offers me solution to solve spark storage problem
  • It adds more complexity of my application since multiple tech softwares are involved.
  • More types of bugs will be encountered when doing streamliner, including hardware connection.
Tianwen Chu profile photo

Pricing Details

Amazon DynamoDB

General

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

MemSQL

General

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

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